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# ScriptIntrinsicBLAS

`public final class ScriptIntrinsicBLAS`
`` `` `` `extends ScriptIntrinsic` ``

java.lang.Object
↳ | android.renderscript.BaseObj
| ↳ | android.renderscript.Script
|  | ↳ | android.renderscript.ScriptIntrinsic
|  |  | ↳ | android.renderscript.ScriptIntrinsicBLAS

This class is deprecated.
Renderscript has been deprecated in API level 31. Please refer to the migration guide for the proposed alternatives.

ScriptIntrinsicBLAS class provides high performance RenderScript APIs to BLAS. The BLAS (Basic Linear Algebra Subprograms) are routines that provide standard building blocks for performing basic vector and matrix operations. For detailed description of BLAS, please refer to http://www.netlib.org/blas/

## Summary

### Constants
`int` | `CONJ_TRANSPOSE`
`int` | `LEFT`
`int` | `LOWER`
`int` | `NON_UNIT`
`int` | `NO_TRANSPOSE`
`int` | `RIGHT`
`int` | `TRANSPOSE`
`int` | `UNIT`
`int` | `UPPER`

### Public methods
`void` | `BNNM(Allocation A, int a_offset, Allocation B, int b_offset, Allocation C, int c_offset, int c_mult)` 8-bit GEMM-like operation for neural networks: C = A * Transpose(B) Calculations are done in 1.10.21 fixed-point format for the final output, just before there's a shift down to drop the fractional parts.
`void` | `CGBMV(int TransA, int KL, int KU, Float2 alpha, Allocation A, Allocation X, int incX, Float2 beta, Allocation Y, int incY)` CGBMV performs one of the matrix-vector operations y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y or y := alpha*A**H*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d0/d75/cgbmv_8f.html Note: For a M*N matrix, the input Allocation should also be of size M*N (dimY = M, dimX = N), but only the region M*(KL+KU+1) will be referenced.
`void` | `CGEMM(int TransA, int TransB, Float2 alpha, Allocation A, Allocation B, Float2 beta, Allocation C)` CGEMM performs one of the matrix-matrix operations C := alpha*op(A)*op(B) + beta*C where op(X) is one of op(X) = X or op(X) = X**T or op(X) = X**H Details: http://www.netlib.org/lapack/explore-html/d6/d5b/cgemm_8f.html
`void` | `CGEMV(int TransA, Float2 alpha, Allocation A, Allocation X, int incX, Float2 beta, Allocation Y, int incY)` CGEMV performs one of the matrix-vector operations y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y or y := alpha*A**H*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d4/d8a/cgemv_8f.html
`void` | `CGERC(Float2 alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A)` CGERC performs the rank 1 operation A := alpha*x*y**H + A Details: http://www.netlib.org/lapack/explore-html/dd/d84/cgerc_8f.html
`void` | `CGERU(Float2 alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A)` CGERU performs the rank 1 operation A := alpha*x*y**T + A Details: http://www.netlib.org/lapack/explore-html/db/d5f/cgeru_8f.html
`void` | `CHBMV(int Uplo, int K, Float2 alpha, Allocation A, Allocation X, int incX, Float2 beta, Allocation Y, int incY)` CHBMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/db/dc2/chbmv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced.
`void` | `CHEMM(int Side, int Uplo, Float2 alpha, Allocation A, Allocation B, Float2 beta, Allocation C)` CHEMM performs one of the matrix-matrix operations C := alpha*A*B + beta*C or C := alpha*B*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d3/d66/chemm_8f.html
`void` | `CHEMV(int Uplo, Float2 alpha, Allocation A, Allocation X, int incX, Float2 beta, Allocation Y, int incY)` CHEMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d7/d51/chemv_8f.html
`void` | `CHER(int Uplo, float alpha, Allocation X, int incX, Allocation A)` CHER performs the rank 1 operation A := alpha*x*x**H + A Details: http://www.netlib.org/lapack/explore-html/d3/d6d/cher_8f.html
`void` | `CHER2(int Uplo, Float2 alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A)` CHER2 performs the symmetric rank 2 operation A := alpha*x*y**H + alpha*y*x**H + A Details: http://www.netlib.org/lapack/explore-html/db/d87/cher2_8f.html
`void` | `CHER2K(int Uplo, int Trans, Float2 alpha, Allocation A, Allocation B, float beta, Allocation C)` CHER2K performs one of the hermitian rank 2k operations C := alpha*A*B**H + conjg( alpha )*B*A**H + beta*C or C := alpha*A**H*B + conjg( alpha )*B**H*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d1/d82/cher2k_8f.html
`void` | `CHERK(int Uplo, int Trans, float alpha, Allocation A, float beta, Allocation C)` CHERK performs one of the hermitian rank k operations C := alpha*A*A**H + beta*C or C := alpha*A**H*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d8/d52/cherk_8f.html
`void` | `CHPMV(int Uplo, Float2 alpha, Allocation Ap, Allocation X, int incX, Float2 beta, Allocation Y, int incY)` CHPMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d2/d06/chpmv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `CHPR(int Uplo, float alpha, Allocation X, int incX, Allocation Ap)` CHPR performs the rank 1 operation A := alpha*x*x**H + A Details: http://www.netlib.org/lapack/explore-html/db/dcd/chpr_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `CHPR2(int Uplo, Float2 alpha, Allocation X, int incX, Allocation Y, int incY, Allocation Ap)` CHPR2 performs the symmetric rank 2 operation A := alpha*x*y**H + alpha*y*x**H + A Details: http://www.netlib.org/lapack/explore-html/d6/d44/chpr2_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `CSYMM(int Side, int Uplo, Float2 alpha, Allocation A, Allocation B, Float2 beta, Allocation C)` CSYMM performs one of the matrix-matrix operations C := alpha*A*B + beta*C or C := alpha*B*A + beta*C Details: http://www.netlib.org/lapack/explore-html/db/d59/csymm_8f.html
`void` | `CSYR2K(int Uplo, int Trans, Float2 alpha, Allocation A, Allocation B, Float2 beta, Allocation C)` CSYR2K performs one of the symmetric rank 2k operations C := alpha*A*B**T + alpha*B*A**T + beta*C or C := alpha*A**T*B + alpha*B**T*A + beta*C Details: http://www.netlib.org/lapack/explore-html/de/d7e/csyr2k_8f.html
`void` | `CSYRK(int Uplo, int Trans, Float2 alpha, Allocation A, Float2 beta, Allocation C)` CSYRK performs one of the symmetric rank k operations C := alpha*A*A**T + beta*C or C := alpha*A**T*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d3/d6a/csyrk_8f.html
`void` | `CTBMV(int Uplo, int TransA, int Diag, int K, Allocation A, Allocation X, int incX)` CTBMV performs one of the matrix-vector operations x := A*x or x := A**T*x or x := A**H*x Details: http://www.netlib.org/lapack/explore-html/d3/dcd/ctbmv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced.
`void` | `CTBSV(int Uplo, int TransA, int Diag, int K, Allocation A, Allocation X, int incX)` CTBSV solves one of the systems of equations A*x = b or A**T*x = b or A**H*x = b Details: http://www.netlib.org/lapack/explore-html/d9/d5f/ctbsv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced.
`void` | `CTPMV(int Uplo, int TransA, int Diag, Allocation Ap, Allocation X, int incX)` CTPMV performs one of the matrix-vector operations x := A*x or x := A**T*x or x := A**H*x Details: http://www.netlib.org/lapack/explore-html/d4/dbb/ctpmv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `CTPSV(int Uplo, int TransA, int Diag, Allocation Ap, Allocation X, int incX)` CTPSV solves one of the systems of equations A*x = b or A**T*x = b or A**H*x = b Details: http://www.netlib.org/lapack/explore-html/d8/d56/ctpsv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `CTRMM(int Side, int Uplo, int TransA, int Diag, Float2 alpha, Allocation A, Allocation B)` CTRMM performs one of the matrix-matrix operations B := alpha*op(A)*B or B := alpha*B*op(A) op(A) is one of op(A) = A or op(A) = A**T or op(A) = A**H Details: http://www.netlib.org/lapack/explore-html/d4/d9b/ctrmm_8f.html
`void` | `CTRMV(int Uplo, int TransA, int Diag, Allocation A, Allocation X, int incX)` CTRMV performs one of the matrix-vector operations x := A*x or x := A**T*x or x := A**H*x Details: http://www.netlib.org/lapack/explore-html/df/d78/ctrmv_8f.html
`void` | `CTRSM(int Side, int Uplo, int TransA, int Diag, Float2 alpha, Allocation A, Allocation B)` CTRSM solves one of the matrix equations op(A)*X := alpha*B or X*op(A) := alpha*B op(A) is one of op(A) = A or op(A) = A**T or op(A) = A**H Details: http://www.netlib.org/lapack/explore-html/de/d30/ctrsm_8f.html
`void` | `CTRSV(int Uplo, int TransA, int Diag, Allocation A, Allocation X, int incX)` CTRSV solves one of the systems of equations A*x = b or A**T*x = b or A**H*x = b Details: http://www.netlib.org/lapack/explore-html/d4/dc8/ctrsv_8f.html
`void` | `DGBMV(int TransA, int KL, int KU, double alpha, Allocation A, Allocation X, int incX, double beta, Allocation Y, int incY)` DGBMV performs one of the matrix-vector operations y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d2/d3f/dgbmv_8f.html Note: For a M*N matrix, the input Allocation should also be of size M*N (dimY = M, dimX = N), but only the region M*(KL+KU+1) will be referenced.
`void` | `DGEMM(int TransA, int TransB, double alpha, Allocation A, Allocation B, double beta, Allocation C)` DGEMM performs one of the matrix-matrix operations C := alpha*op(A)*op(B) + beta*C where op(X) is one of op(X) = X or op(X) = X**T Details: http://www.netlib.org/lapack/explore-html/d7/d2b/dgemm_8f.html
`void` | `DGEMV(int TransA, double alpha, Allocation A, Allocation X, int incX, double beta, Allocation Y, int incY)` DGEMV performs one of the matrix-vector operations y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y Details: http://www.netlib.org/lapack/explore-html/dc/da8/dgemv_8f.html
`void` | `DGER(double alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A)` DGER performs the rank 1 operation A := alpha*x*y**T + A Details: http://www.netlib.org/lapack/explore-html/dc/da8/dger_8f.html
`void` | `DSBMV(int Uplo, int K, double alpha, Allocation A, Allocation X, int incX, double beta, Allocation Y, int incY)` DSBMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d8/d1e/dsbmv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced.
`void` | `DSPMV(int Uplo, double alpha, Allocation Ap, Allocation X, int incX, double beta, Allocation Y, int incY)` DSPMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d4/d85/dspmv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `DSPR(int Uplo, double alpha, Allocation X, int incX, Allocation Ap)` DSPR performs the rank 1 operation A := alpha*x*x**T + A Details: http://www.netlib.org/lapack/explore-html/dd/dba/dspr_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `DSPR2(int Uplo, double alpha, Allocation X, int incX, Allocation Y, int incY, Allocation Ap)` DSPR2 performs the symmetric rank 2 operation A := alpha*x*y**T + alpha*y*x**T + A Details: http://www.netlib.org/lapack/explore-html/dd/d9e/dspr2_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `DSYMM(int Side, int Uplo, double alpha, Allocation A, Allocation B, double beta, Allocation C)` DSYMM performs one of the matrix-matrix operations C := alpha*A*B + beta*C or C := alpha*B*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d8/db0/dsymm_8f.html
`void` | `DSYMV(int Uplo, double alpha, Allocation A, Allocation X, int incX, double beta, Allocation Y, int incY)` DSYMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d8/dbe/dsymv_8f.html
`void` | `DSYR(int Uplo, double alpha, Allocation X, int incX, Allocation A)` DSYR performs the rank 1 operation A := alpha*x*x**T + A Details: http://www.netlib.org/lapack/explore-html/d3/d60/dsyr_8f.html
`void` | `DSYR2(int Uplo, double alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A)` DSYR2 performs the symmetric rank 2 operation A := alpha*x*y**T + alpha*y*x**T + A Details: http://www.netlib.org/lapack/explore-html/de/d41/dsyr2_8f.html
`void` | `DSYR2K(int Uplo, int Trans, double alpha, Allocation A, Allocation B, double beta, Allocation C)` DSYR2K performs one of the symmetric rank 2k operations C := alpha*A*B**T + alpha*B*A**T + beta*C or C := alpha*A**T*B + alpha*B**T*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d1/dec/dsyr2k_8f.html
`void` | `DSYRK(int Uplo, int Trans, double alpha, Allocation A, double beta, Allocation C)` DSYRK performs one of the symmetric rank k operations C := alpha*A*A**T + beta*C or C := alpha*A**T*A + beta*C Details: http://www.netlib.org/lapack/explore-html/dc/d05/dsyrk_8f.html
`void` | `DTBMV(int Uplo, int TransA, int Diag, int K, Allocation A, Allocation X, int incX)` DTBMV performs one of the matrix-vector operations x := A*x or x := A**T*x Details: http://www.netlib.org/lapack/explore-html/df/d29/dtbmv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced.
`void` | `DTBSV(int Uplo, int TransA, int Diag, int K, Allocation A, Allocation X, int incX)` DTBSV solves one of the systems of equations A*x = b or A**T*x = b Details: http://www.netlib.org/lapack/explore-html/d4/dcf/dtbsv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced.
`void` | `DTPMV(int Uplo, int TransA, int Diag, Allocation Ap, Allocation X, int incX)` DTPMV performs one of the matrix-vector operations x := A*x or x := A**T*x Details: http://www.netlib.org/lapack/explore-html/dc/dcd/dtpmv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `DTPSV(int Uplo, int TransA, int Diag, Allocation Ap, Allocation X, int incX)` DTPSV solves one of the systems of equations A*x = b or A**T*x = b Details: http://www.netlib.org/lapack/explore-html/d9/d84/dtpsv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `DTRMM(int Side, int Uplo, int TransA, int Diag, double alpha, Allocation A, Allocation B)` DTRMM performs one of the matrix-matrix operations B := alpha*op(A)*B or B := alpha*B*op(A) op(A) is one of op(A) = A or op(A) = A**T Details: http://www.netlib.org/lapack/explore-html/dd/d19/dtrmm_8f.html
`void` | `DTRMV(int Uplo, int TransA, int Diag, Allocation A, Allocation X, int incX)` DTRMV performs one of the matrix-vector operations x := A*x or x := A**T*x Details: http://www.netlib.org/lapack/explore-html/dc/d7e/dtrmv_8f.html
`void` | `DTRSM(int Side, int Uplo, int TransA, int Diag, double alpha, Allocation A, Allocation B)` DTRSM solves one of the matrix equations op(A)*X := alpha*B or X*op(A) := alpha*B op(A) is one of op(A) = A or op(A) = A**T Details: http://www.netlib.org/lapack/explore-html/de/da7/dtrsm_8f.html
`void` | `DTRSV(int Uplo, int TransA, int Diag, Allocation A, Allocation X, int incX)` DTRSV solves one of the systems of equations A*x = b or A**T*x = b Details: http://www.netlib.org/lapack/explore-html/d6/d96/dtrsv_8f.html
`void` | `SGBMV(int TransA, int KL, int KU, float alpha, Allocation A, Allocation X, int incX, float beta, Allocation Y, int incY)` SGBMV performs one of the matrix-vector operations y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d6/d46/sgbmv_8f.html Note: For a M*N matrix, the input Allocation should also be of size M*N (dimY = M, dimX = N), but only the region M*(KL+KU+1) will be referenced.
`void` | `SGEMM(int TransA, int TransB, float alpha, Allocation A, Allocation B, float beta, Allocation C)` SGEMM performs one of the matrix-matrix operations C := alpha*op(A)*op(B) + beta*C where op(X) is one of op(X) = X or op(X) = X**T Details: http://www.netlib.org/lapack/explore-html/d4/de2/sgemm_8f.html
`void` | `SGEMV(int TransA, float alpha, Allocation A, Allocation X, int incX, float beta, Allocation Y, int incY)` SGEMV performs one of the matrix-vector operations y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y Details: http://www.netlib.org/lapack/explore-html/db/d58/sgemv_8f.html
`void` | `SGER(float alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A)` SGER performs the rank 1 operation A := alpha*x*y**T + A Details: http://www.netlib.org/lapack/explore-html/db/d5c/sger_8f.html
`void` | `SSBMV(int Uplo, int K, float alpha, Allocation A, Allocation X, int incX, float beta, Allocation Y, int incY)` SSBMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d3/da1/ssbmv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced.
`void` | `SSPMV(int Uplo, float alpha, Allocation Ap, Allocation X, int incX, float beta, Allocation Y, int incY)` SSPMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d8/d68/sspmv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `SSPR(int Uplo, float alpha, Allocation X, int incX, Allocation Ap)` SSPR performs the rank 1 operation A := alpha*x*x**T + A Details: http://www.netlib.org/lapack/explore-html/d2/d9b/sspr_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `SSPR2(int Uplo, float alpha, Allocation X, int incX, Allocation Y, int incY, Allocation Ap)` SSPR2 performs the symmetric rank 2 operation A := alpha*x*y**T + alpha*y*x**T + A Details: http://www.netlib.org/lapack/explore-html/db/d3e/sspr2_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `SSYMM(int Side, int Uplo, float alpha, Allocation A, Allocation B, float beta, Allocation C)` SSYMM performs one of the matrix-matrix operations C := alpha*A*B + beta*C or C := alpha*B*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d7/d42/ssymm_8f.html
`void` | `SSYMV(int Uplo, float alpha, Allocation A, Allocation X, int incX, float beta, Allocation Y, int incY)` SSYMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d2/d94/ssymv_8f.html
`void` | `SSYR(int Uplo, float alpha, Allocation X, int incX, Allocation A)` SSYR performs the rank 1 operation A := alpha*x*x**T + A Details: http://www.netlib.org/lapack/explore-html/d6/dac/ssyr_8f.html
`void` | `SSYR2(int Uplo, float alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A)` SSYR2 performs the symmetric rank 2 operation A := alpha*x*y**T + alpha*y*x**T + A Details: http://www.netlib.org/lapack/explore-html/db/d99/ssyr2_8f.html
`void` | `SSYR2K(int Uplo, int Trans, float alpha, Allocation A, Allocation B, float beta, Allocation C)` SSYR2K performs one of the symmetric rank 2k operations C := alpha*A*B**T + alpha*B*A**T + beta*C or C := alpha*A**T*B + alpha*B**T*A + beta*C Details: http://www.netlib.org/lapack/explore-html/df/d3d/ssyr2k_8f.html
`void` | `SSYRK(int Uplo, int Trans, float alpha, Allocation A, float beta, Allocation C)` SSYRK performs one of the symmetric rank k operations C := alpha*A*A**T + beta*C or C := alpha*A**T*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d0/d40/ssyrk_8f.html
`void` | `STBMV(int Uplo, int TransA, int Diag, int K, Allocation A, Allocation X, int incX)` STBMV performs one of the matrix-vector operations x := A*x or x := A**T*x Details: http://www.netlib.org/lapack/explore-html/d6/d7d/stbmv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced.
`void` | `STBSV(int Uplo, int TransA, int Diag, int K, Allocation A, Allocation X, int incX)` STBSV solves one of the systems of equations A*x = b or A**T*x = b Details: http://www.netlib.org/lapack/explore-html/d0/d1f/stbsv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced.
`void` | `STPMV(int Uplo, int TransA, int Diag, Allocation Ap, Allocation X, int incX)` STPMV performs one of the matrix-vector operations x := A*x or x := A**T*x Details: http://www.netlib.org/lapack/explore-html/db/db1/stpmv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `STPSV(int Uplo, int TransA, int Diag, Allocation Ap, Allocation X, int incX)` STPSV solves one of the systems of equations A*x = b or A**T*x = b Details: http://www.netlib.org/lapack/explore-html/d0/d7c/stpsv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `STRMM(int Side, int Uplo, int TransA, int Diag, float alpha, Allocation A, Allocation B)` STRMM performs one of the matrix-matrix operations B := alpha*op(A)*B or B := alpha*B*op(A) op(A) is one of op(A) = A or op(A) = A**T Details: http://www.netlib.org/lapack/explore-html/df/d01/strmm_8f.html
`void` | `STRMV(int Uplo, int TransA, int Diag, Allocation A, Allocation X, int incX)` STRMV performs one of the matrix-vector operations x := A*x or x := A**T*x Details: http://www.netlib.org/lapack/explore-html/de/d45/strmv_8f.html
`void` | `STRSM(int Side, int Uplo, int TransA, int Diag, float alpha, Allocation A, Allocation B)` STRSM solves one of the matrix equations op(A)*X := alpha*B or X*op(A) := alpha*B op(A) is one of op(A) = A or op(A) = A**T Details: http://www.netlib.org/lapack/explore-html/d2/d8b/strsm_8f.html
`void` | `STRSV(int Uplo, int TransA, int Diag, Allocation A, Allocation X, int incX)` STRSV solves one of the systems of equations A*x = b or A**T*x = b Details: http://www.netlib.org/lapack/explore-html/d0/d2a/strsv_8f.html
`void` | `ZGBMV(int TransA, int KL, int KU, Double2 alpha, Allocation A, Allocation X, int incX, Double2 beta, Allocation Y, int incY)` ZGBMV performs one of the matrix-vector operations y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y or y := alpha*A**H*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d9/d46/zgbmv_8f.html Note: For a M*N matrix, the input Allocation should also be of size M*N (dimY = M, dimX = N), but only the region M*(KL+KU+1) will be referenced.
`void` | `ZGEMM(int TransA, int TransB, Double2 alpha, Allocation A, Allocation B, Double2 beta, Allocation C)` ZGEMM performs one of the matrix-matrix operations C := alpha*op(A)*op(B) + beta*C where op(X) is one of op(X) = X or op(X) = X**T or op(X) = X**H Details: http://www.netlib.org/lapack/explore-html/d7/d76/zgemm_8f.html
`void` | `ZGEMV(int TransA, Double2 alpha, Allocation A, Allocation X, int incX, Double2 beta, Allocation Y, int incY)` ZGEMV performs one of the matrix-vector operations y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y or y := alpha*A**H*x + beta*y Details: http://www.netlib.org/lapack/explore-html/db/d40/zgemv_8f.html
`void` | `ZGERC(Double2 alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A)` ZGERC performs the rank 1 operation A := alpha*x*y**H + A Details: http://www.netlib.org/lapack/explore-html/d3/dad/zgerc_8f.html
`void` | `ZGERU(Double2 alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A)` ZGERU performs the rank 1 operation A := alpha*x*y**T + A Details: http://www.netlib.org/lapack/explore-html/d7/d12/zgeru_8f.html
`void` | `ZHBMV(int Uplo, int K, Double2 alpha, Allocation A, Allocation X, int incX, Double2 beta, Allocation Y, int incY)` ZHBMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d3/d1a/zhbmv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced.
`void` | `ZHEMM(int Side, int Uplo, Double2 alpha, Allocation A, Allocation B, Double2 beta, Allocation C)` ZHEMM performs one of the matrix-matrix operations C := alpha*A*B + beta*C or C := alpha*B*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d6/d3e/zhemm_8f.html
`void` | `ZHEMV(int Uplo, Double2 alpha, Allocation A, Allocation X, int incX, Double2 beta, Allocation Y, int incY)` ZHEMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d0/ddd/zhemv_8f.html
`void` | `ZHER(int Uplo, double alpha, Allocation X, int incX, Allocation A)` ZHER performs the rank 1 operation A := alpha*x*x**H + A Details: http://www.netlib.org/lapack/explore-html/de/d0e/zher_8f.html
`void` | `ZHER2(int Uplo, Double2 alpha, Allocation X, int incX, Allocation Y, int incY, Allocation A)` ZHER2 performs the symmetric rank 2 operation A := alpha*x*y**H + alpha*y*x**H + A Details: http://www.netlib.org/lapack/explore-html/da/d8a/zher2_8f.html
`void` | `ZHER2K(int Uplo, int Trans, Double2 alpha, Allocation A, Allocation B, double beta, Allocation C)` ZHER2K performs one of the hermitian rank 2k operations C := alpha*A*B**H + conjg( alpha )*B*A**H + beta*C or C := alpha*A**H*B + conjg( alpha )*B**H*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d7/dfa/zher2k_8f.html
`void` | `ZHERK(int Uplo, int Trans, double alpha, Allocation A, double beta, Allocation C)` ZHERK performs one of the hermitian rank k operations C := alpha*A*A**H + beta*C or C := alpha*A**H*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d1/db1/zherk_8f.html
`void` | `ZHPMV(int Uplo, Double2 alpha, Allocation Ap, Allocation X, int incX, Double2 beta, Allocation Y, int incY)` ZHPMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d0/d60/zhpmv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `ZHPR(int Uplo, double alpha, Allocation X, int incX, Allocation Ap)` ZHPR performs the rank 1 operation A := alpha*x*x**H + A Details: http://www.netlib.org/lapack/explore-html/de/de1/zhpr_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `ZHPR2(int Uplo, Double2 alpha, Allocation X, int incX, Allocation Y, int incY, Allocation Ap)` ZHPR2 performs the symmetric rank 2 operation A := alpha*x*y**H + alpha*y*x**H + A Details: http://www.netlib.org/lapack/explore-html/d5/d52/zhpr2_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `ZSYMM(int Side, int Uplo, Double2 alpha, Allocation A, Allocation B, Double2 beta, Allocation C)` ZSYMM performs one of the matrix-matrix operations C := alpha*A*B + beta*C or C := alpha*B*A + beta*C Details: http://www.netlib.org/lapack/explore-html/df/d51/zsymm_8f.html
`void` | `ZSYR2K(int Uplo, int Trans, Double2 alpha, Allocation A, Allocation B, Double2 beta, Allocation C)` ZSYR2K performs one of the symmetric rank 2k operations C := alpha*A*B**T + alpha*B*A**T + beta*C or C := alpha*A**T*B + alpha*B**T*A + beta*C Details: http://www.netlib.org/lapack/explore-html/df/d20/zsyr2k_8f.html
`void` | `ZSYRK(int Uplo, int Trans, Double2 alpha, Allocation A, Double2 beta, Allocation C)` ZSYRK performs one of the symmetric rank k operations C := alpha*A*A**T + beta*C or C := alpha*A**T*A + beta*C Details: http://www.netlib.org/lapack/explore-html/de/d54/zsyrk_8f.html
`void` | `ZTBMV(int Uplo, int TransA, int Diag, int K, Allocation A, Allocation X, int incX)` ZTBMV performs one of the matrix-vector operations x := A*x or x := A**T*x or x := A**H*x Details: http://www.netlib.org/lapack/explore-html/d3/d39/ztbmv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced.
`void` | `ZTBSV(int Uplo, int TransA, int Diag, int K, Allocation A, Allocation X, int incX)` ZTBSV solves one of the systems of equations A*x = b or A**T*x = b or A**H*x = b Details: http://www.netlib.org/lapack/explore-html/d4/d5a/ztbsv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced.
`void` | `ZTPMV(int Uplo, int TransA, int Diag, Allocation Ap, Allocation X, int incX)` ZTPMV performs one of the matrix-vector operations x := A*x or x := A**T*x or x := A**H*x Details: http://www.netlib.org/lapack/explore-html/d2/d9e/ztpmv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `ZTPSV(int Uplo, int TransA, int Diag, Allocation Ap, Allocation X, int incX)` ZTPSV solves one of the systems of equations A*x = b or A**T*x = b or A**H*x = b Details: http://www.netlib.org/lapack/explore-html/da/d57/ztpsv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'.
`void` | `ZTRMM(int Side, int Uplo, int TransA, int Diag, Double2 alpha, Allocation A, Allocation B)` ZTRMM performs one of the matrix-matrix operations B := alpha*op(A)*B or B := alpha*B*op(A) op(A) is one of op(A) = A or op(A) = A**T or op(A) = A**H Details: http://www.netlib.org/lapack/explore-html/d8/de1/ztrmm_8f.html
`void` | `ZTRMV(int Uplo, int TransA, int Diag, Allocation A, Allocation X, int incX)` ZTRMV performs one of the matrix-vector operations x := A*x or x := A**T*x or x := A**H*x Details: http://www.netlib.org/lapack/explore-html/d0/dd1/ztrmv_8f.html
`void` | `ZTRSM(int Side, int Uplo, int TransA, int Diag, Double2 alpha, Allocation A, Allocation B)` ZTRSM solves one of the matrix equations op(A)*X := alpha*B or X*op(A) := alpha*B op(A) is one of op(A) = A or op(A) = A**T or op(A) = A**H Details: http://www.netlib.org/lapack/explore-html/d1/d39/ztrsm_8f.html
`void` | `ZTRSV(int Uplo, int TransA, int Diag, Allocation A, Allocation X, int incX)` ZTRSV solves one of the systems of equations A*x = b or A**T*x = b or A**H*x = b Details: http://www.netlib.org/lapack/explore-html/d1/d2f/ztrsv_8f.html
`static ScriptIntrinsicBLAS` | `create(RenderScript rs)` Create an intrinsic to access BLAS subroutines.

### Inherited methods
From class `android.renderscript.Script`
`void` | `bindAllocation(Allocation va, int slot)` Only intended for use by generated reflected code.
`Script.FieldID` | `createFieldID(int slot, Element e)` Only to be used by generated reflected classes.
`Script.InvokeID` | `createInvokeID(int slot)` Only to be used by generated reflected classes.
`Script.KernelID` | `createKernelID(int slot, int sig, Element ein, Element eout)` Only to be used by generated reflected classes.
`void` | `forEach(int slot, Allocation[] ains, Allocation aout, FieldPacker v)` Only intended for use by generated reflected code.
`void` | `forEach(int slot, Allocation ain, Allocation aout, FieldPacker v, Script.LaunchOptions sc)` Only intended for use by generated reflected code.
`void` | `forEach(int slot, Allocation ain, Allocation aout, FieldPacker v)` Only intended for use by generated reflected code.
`void` | `forEach(int slot, Allocation[] ains, Allocation aout, FieldPacker v, Script.LaunchOptions sc)` Only intended for use by generated reflected code.
`boolean` | `getVarB(int index)`
`double` | `getVarD(int index)`
`float` | `getVarF(int index)`
`int` | `getVarI(int index)`
`long` | `getVarJ(int index)`
`void` | `getVarV(int index, FieldPacker v)` Only intended for use by generated reflected code.
`void` | `invoke(int slot)` Only intended for use by generated reflected code.
`void` | `invoke(int slot, FieldPacker v)` Only intended for use by generated reflected code.
`void` | `reduce(int slot, Allocation[] ains, Allocation aout, Script.LaunchOptions sc)` Only intended for use by generated reflected code.
`void` | `setTimeZone(String timeZone)`
`void` | `setVar(int index, boolean v)` Only intended for use by generated reflected code.
`void` | `setVar(int index, int v)` Only intended for use by generated reflected code.
`void` | `setVar(int index, FieldPacker v, Element e, int[] dims)` Only intended for use by generated reflected code.
`void` | `setVar(int index, FieldPacker v)` Only intended for use by generated reflected code.
`void` | `setVar(int index, float v)` Only intended for use by generated reflected code.
`void` | `setVar(int index, double v)` Only intended for use by generated reflected code.
`void` | `setVar(int index, long v)` Only intended for use by generated reflected code.
`void` | `setVar(int index, BaseObj o)` Only intended for use by generated reflected code.
From class `android.renderscript.BaseObj`
`void` | `destroy()` Frees any native resources associated with this object.
`boolean` | `equals(Object obj)` Compare the current BaseObj with another BaseObj for equality.
`void` | `finalize()` Called by the garbage collector on an object when garbage collection determines that there are no more references to the object.
`String` | `getName()`
`int` | `hashCode()` Calculates the hash code value for a BaseObj.
`void` | `setName(String name)` setName assigns a name to an object.
From class `java.lang.Object`
`Object` | `clone()` Creates and returns a copy of this object.
`boolean` | `equals(Object obj)` Indicates whether some other object is "equal to" this one.
`void` | `finalize()` Called by the garbage collector on an object when garbage collection determines that there are no more references to the object.
`final Class<?>` | `getClass()` Returns the runtime class of this `Object`.
`int` | `hashCode()` Returns a hash code value for the object.
`final void` | `notify()` Wakes up a single thread that is waiting on this object's monitor.
`final void` | `notifyAll()` Wakes up all threads that are waiting on this object's monitor.
`String` | `toString()` Returns a string representation of the object.
`final void` | `wait(long timeout, int nanos)` Causes the current thread to wait until another thread invokes the `notify()` method or the `notifyAll()` method for this object, or some other thread interrupts the current thread, or a certain amount of real time has elapsed.
`final void` | `wait(long timeout)` Causes the current thread to wait until either another thread invokes the `notify()` method or the `notifyAll()` method for this object, or a specified amount of time has elapsed.
`final void` | `wait()` Causes the current thread to wait until another thread invokes the `notify()` method or the `notifyAll()` method for this object.

## Constants

### CONJ_TRANSPOSE

    public static final int CONJ_TRANSPOSE

Constant Value: 113 (0x00000071)

### LEFT

    public static final int LEFT

Constant Value: 141 (0x0000008d)

### LOWER

    public static final int LOWER

Constant Value: 122 (0x0000007a)

### NON_UNIT

    public static final int NON_UNIT

Constant Value: 131 (0x00000083)

### NO_TRANSPOSE

    public static final int NO_TRANSPOSE

Constant Value: 111 (0x0000006f)

### RIGHT

    public static final int RIGHT

Constant Value: 142 (0x0000008e)

### TRANSPOSE

    public static final int TRANSPOSE

Constant Value: 112 (0x00000070)

### UNIT

    public static final int UNIT

Constant Value: 132 (0x00000084)

### UPPER

    public static final int UPPER

Constant Value: 121 (0x00000079)

## Public methods

### BNNM

    public void BNNM (Allocation A,
                    int a_offset,
                    Allocation B,
                    int b_offset,
                    Allocation C,
                    int c_offset,
                    int c_mult)

8-bit GEMM-like operation for neural networks: C = A * Transpose(B) Calculations are done in 1.10.21 fixed-point format for the final output, just before there's a shift down to drop the fractional parts. The output values are gated to 0 to 255 to fit in a byte, but the 10-bit format gives some headroom to avoid wrapping around on small overflows.

Parameters
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#U8`.
`a_offset` | `int`: The offset for all values in matrix A, e.g A[i,j] = A[i,j] - a_offset. Value should be from 0 to 255.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#U8`.
`b_offset` | `int`: The offset for all values in matrix B, e.g B[i,j] = B[i,j] - b_offset. Value should be from 0 to 255.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#U8`.
`c_offset` | `int`: The offset for all values in matrix C.
`c_mult` | `int`: The multiplier for all values in matrix C, e.g C[i,j] = (C[i,j] + c_offset) * c_mult.

### CGBMV

    public void CGBMV (int TransA,
                    int KL,
                    int KU,
                    Float2 alpha,
                    Allocation A,
                    Allocation X,
                    int incX,
                    Float2 beta,
                    Allocation Y,
                    int incY)

CGBMV performs one of the matrix-vector operations y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y or y := alpha*A**H*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d0/d75/cgbmv_8f.html Note: For a M*N matrix, the input Allocation should also be of size M*N (dimY = M, dimX = N), but only the region M*(KL+KU+1) will be referenced. The following subroutine can is an example showing how to convert the original matrix 'a' to row-based band matrix 'b'. for i in range(0, m): for j in range(max(0, i-kl), min(i+ku+1, n)): b[i, j-i+kl] = a[i, j]

Parameters
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`KL` | `int`: The number of sub-diagonals of the matrix A.
`KU` | `int`: The number of super-diagonals of the matrix A.
`alpha` | `Float2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains the band matrix A, supported elements type `Element#F32_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `Float2`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F32_2`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### CGEMM

    public void CGEMM (int TransA,
                    int TransB,
                    Float2 alpha,
                    Allocation A,
                    Allocation B,
                    Float2 beta,
                    Allocation C)

CGEMM performs one of the matrix-matrix operations C := alpha*op(A)*op(B) + beta*C where op(X) is one of op(X) = X or op(X) = X**T or op(X) = X**H Details: http://www.netlib.org/lapack/explore-html/d6/d5b/cgemm_8f.html

Parameters
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`TransB` | `int`: The type of transpose applied to matrix B. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `Float2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F32_2`.
`beta` | `Float2`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F32_2`.

### CGEMV

    public void CGEMV (int TransA,
                    Float2 alpha,
                    Allocation A,
                    Allocation X,
                    int incX,
                    Float2 beta,
                    Allocation Y,
                    int incY)

CGEMV performs one of the matrix-vector operations y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y or y := alpha*A**H*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d4/d8a/cgemv_8f.html

Parameters
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `Float2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `Float2`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F32_2`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### CGERC

    public void CGERC (Float2 alpha,
                    Allocation X,
                    int incX,
                    Allocation Y,
                    int incY,
                    Allocation A)

CGERC performs the rank 1 operation A := alpha*x*y**H + A Details: http://www.netlib.org/lapack/explore-html/dd/d84/cgerc_8f.html

Parameters
`alpha` | `Float2`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F32_2`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.

### CGERU

    public void CGERU (Float2 alpha,
                    Allocation X,
                    int incX,
                    Allocation Y,
                    int incY,
                    Allocation A)

CGERU performs the rank 1 operation A := alpha*x*y**T + A Details: http://www.netlib.org/lapack/explore-html/db/d5f/cgeru_8f.html

Parameters
`alpha` | `Float2`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F32_2`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.

### CHBMV

    public void CHBMV (int Uplo,
                    int K,
                    Float2 alpha,
                    Allocation A,
                    Allocation X,
                    int incX,
                    Float2 beta,
                    Allocation Y,
                    int incY)

CHBMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/db/dc2/chbmv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced. The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'. for i in range(0, n): for j in range(i, min(i+k+1, n)): b[i, j-i] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of the band matrix A is being supplied. Value is `UPPER`, or `LOWER`
`K` | `int`: The number of off-diagonals of the matrix A
`alpha` | `Float2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `Float2`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F32_2`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### CHEMM

    public void CHEMM (int Side,
                    int Uplo,
                    Float2 alpha,
                    Allocation A,
                    Allocation B,
                    Float2 beta,
                    Allocation C)

CHEMM performs one of the matrix-matrix operations C := alpha*A*B + beta*C or C := alpha*B*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d3/d66/chemm_8f.html

Parameters
`Side` | `int`: Specifies whether the symmetric matrix A appears on the left or right. Value is `LEFT`, or `RIGHT`
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be referenced. Value is `UPPER`, or `LOWER`
`alpha` | `Float2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F32_2`.
`beta` | `Float2`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F32_2`.

### CHEMV

    public void CHEMV (int Uplo,
                    Float2 alpha,
                    Allocation A,
                    Allocation X,
                    int incX,
                    Float2 beta,
                    Allocation Y,
                    int incY)

CHEMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d7/d51/chemv_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be referenced. Value is `UPPER`, or `LOWER`
`alpha` | `Float2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `Float2`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F32_2`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### CHER

    public void CHER (int Uplo,
                    float alpha,
                    Allocation X,
                    int incX,
                    Allocation A)

CHER performs the rank 1 operation A := alpha*x*x**H + A Details: http://www.netlib.org/lapack/explore-html/d3/d6d/cher_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be referenced. Value is `UPPER`, or `LOWER`
`alpha` | `float`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.

### CHER2

    public void CHER2 (int Uplo,
                    Float2 alpha,
                    Allocation X,
                    int incX,
                    Allocation Y,
                    int incY,
                    Allocation A)

CHER2 performs the symmetric rank 2 operation A := alpha*x*y**H + alpha*y*x**H + A Details: http://www.netlib.org/lapack/explore-html/db/d87/cher2_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be referenced. Value is `UPPER`, or `LOWER`
`alpha` | `Float2`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F32_2`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.

### CHER2K

    public void CHER2K (int Uplo,
                    int Trans,
                    Float2 alpha,
                    Allocation A,
                    Allocation B,
                    float beta,
                    Allocation C)

CHER2K performs one of the hermitian rank 2k operations C := alpha*A*B**H + conjg( alpha )*B*A**H + beta*C or C := alpha*A**H*B + conjg( alpha )*B**H*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d1/d82/cher2k_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of C is to be referenced. Value is `UPPER`, or `LOWER`
`Trans` | `int`: The type of transpose applied to the operation. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `Float2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F32_2`.
`beta` | `float`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F32_2`.

### CHERK

    public void CHERK (int Uplo,
                    int Trans,
                    float alpha,
                    Allocation A,
                    float beta,
                    Allocation C)

CHERK performs one of the hermitian rank k operations C := alpha*A*A**H + beta*C or C := alpha*A**H*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d8/d52/cherk_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of C is to be referenced. Value is `UPPER`, or `LOWER`
`Trans` | `int`: The type of transpose applied to the operation. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `float`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.
`beta` | `float`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F32_2`.

### CHPMV

    public void CHPMV (int Uplo,
                    Float2 alpha,
                    Allocation Ap,
                    Allocation X,
                    int incX,
                    Float2 beta,
                    Allocation Y,
                    int incY)

CHPMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d2/d06/chpmv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of the matrix A is supplied in packed form. Value is `UPPER`, or `LOWER`
`alpha` | `Float2`: The scalar alpha.
`Ap` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `Float2`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F32_2`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### CHPR

    public void CHPR (int Uplo,
                    float alpha,
                    Allocation X,
                    int incX,
                    Allocation Ap)

CHPR performs the rank 1 operation A := alpha*x*x**H + A Details: http://www.netlib.org/lapack/explore-html/db/dcd/chpr_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be supplied in the packed form. Value is `UPPER`, or `LOWER`
`alpha` | `float`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`Ap` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.

### CHPR2

    public void CHPR2 (int Uplo,
                    Float2 alpha,
                    Allocation X,
                    int incX,
                    Allocation Y,
                    int incY,
                    Allocation Ap)

CHPR2 performs the symmetric rank 2 operation A := alpha*x*y**H + alpha*y*x**H + A Details: http://www.netlib.org/lapack/explore-html/d6/d44/chpr2_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be supplied in the packed form. Value is `UPPER`, or `LOWER`
`alpha` | `Float2`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F32_2`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.
`Ap` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.

### CSYMM

    public void CSYMM (int Side,
                    int Uplo,
                    Float2 alpha,
                    Allocation A,
                    Allocation B,
                    Float2 beta,
                    Allocation C)

CSYMM performs one of the matrix-matrix operations C := alpha*A*B + beta*C or C := alpha*B*A + beta*C Details: http://www.netlib.org/lapack/explore-html/db/d59/csymm_8f.html

Parameters
`Side` | `int`: Specifies whether the symmetric matrix A appears on the left or right. Value is `LEFT`, or `RIGHT`
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be referenced. Value is `UPPER`, or `LOWER`
`alpha` | `Float2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F32_2`.
`beta` | `Float2`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F32_2`.

### CSYR2K

    public void CSYR2K (int Uplo,
                    int Trans,
                    Float2 alpha,
                    Allocation A,
                    Allocation B,
                    Float2 beta,
                    Allocation C)

CSYR2K performs one of the symmetric rank 2k operations C := alpha*A*B**T + alpha*B*A**T + beta*C or C := alpha*A**T*B + alpha*B**T*A + beta*C Details: http://www.netlib.org/lapack/explore-html/de/d7e/csyr2k_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of C is to be referenced. Value is `UPPER`, or `LOWER`
`Trans` | `int`: The type of transpose applied to the operation. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `Float2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F32_2`.
`beta` | `Float2`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F32_2`.

### CSYRK

    public void CSYRK (int Uplo,
                    int Trans,
                    Float2 alpha,
                    Allocation A,
                    Float2 beta,
                    Allocation C)

CSYRK performs one of the symmetric rank k operations C := alpha*A*A**T + beta*C or C := alpha*A**T*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d3/d6a/csyrk_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of C is to be referenced. Value is `UPPER`, or `LOWER`
`Trans` | `int`: The type of transpose applied to the operation. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `Float2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.
`beta` | `Float2`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F32_2`.

### CTBMV

    public void CTBMV (int Uplo,
                    int TransA,
                    int Diag,
                    int K,
                    Allocation A,
                    Allocation X,
                    int incX)

CTBMV performs one of the matrix-vector operations x := A*x or x := A**T*x or x := A**H*x Details: http://www.netlib.org/lapack/explore-html/d3/dcd/ctbmv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced. The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'. for i in range(0, n): for j in range(i, min(i+k+1, n)): b[i, j-i] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`K` | `int`: The number of off-diagonals of the matrix A
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### CTBSV

    public void CTBSV (int Uplo,
                    int TransA,
                    int Diag,
                    int K,
                    Allocation A,
                    Allocation X,
                    int incX)

CTBSV solves one of the systems of equations A*x = b or A**T*x = b or A**H*x = b Details: http://www.netlib.org/lapack/explore-html/d9/d5f/ctbsv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced. The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'. for i in range(0, n): for j in range(i, min(i+k+1, n)): b[i, j-i] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`K` | `int`: The number of off-diagonals of the matrix A
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### CTPMV

    public void CTPMV (int Uplo,
                    int TransA,
                    int Diag,
                    Allocation Ap,
                    Allocation X,
                    int incX)

CTPMV performs one of the matrix-vector operations x := A*x or x := A**T*x or x := A**H*x Details: http://www.netlib.org/lapack/explore-html/d4/dbb/ctpmv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`Ap` | `Allocation`: The input allocation contains packed matrix A, supported elements type `Element#F32_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### CTPSV

    public void CTPSV (int Uplo,
                    int TransA,
                    int Diag,
                    Allocation Ap,
                    Allocation X,
                    int incX)

CTPSV solves one of the systems of equations A*x = b or A**T*x = b or A**H*x = b Details: http://www.netlib.org/lapack/explore-html/d8/d56/ctpsv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`Ap` | `Allocation`: The input allocation contains packed matrix A, supported elements type `Element#F32_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### CTRMM

    public void CTRMM (int Side,
                    int Uplo,
                    int TransA,
                    int Diag,
                    Float2 alpha,
                    Allocation A,
                    Allocation B)

CTRMM performs one of the matrix-matrix operations B := alpha*op(A)*B or B := alpha*B*op(A) op(A) is one of op(A) = A or op(A) = A**T or op(A) = A**H Details: http://www.netlib.org/lapack/explore-html/d4/d9b/ctrmm_8f.html

Parameters
`Side` | `int`: Specifies whether the symmetric matrix A appears on the left or right. Value is `LEFT`, or `RIGHT`
`Uplo` | `int`: Specifies whether matrix A is upper or lower triangular. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`alpha` | `Float2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F32_2`.

### CTRMV

    public void CTRMV (int Uplo,
                    int TransA,
                    int Diag,
                    Allocation A,
                    Allocation X,
                    int incX)

CTRMV performs one of the matrix-vector operations x := A*x or x := A**T*x or x := A**H*x Details: http://www.netlib.org/lapack/explore-html/df/d78/ctrmv_8f.html

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### CTRSM

    public void CTRSM (int Side,
                    int Uplo,
                    int TransA,
                    int Diag,
                    Float2 alpha,
                    Allocation A,
                    Allocation B)

CTRSM solves one of the matrix equations op(A)*X := alpha*B or X*op(A) := alpha*B op(A) is one of op(A) = A or op(A) = A**T or op(A) = A**H Details: http://www.netlib.org/lapack/explore-html/de/d30/ctrsm_8f.html

Parameters
`Side` | `int`: Specifies whether the symmetric matrix A appears on the left or right. Value is `LEFT`, or `RIGHT`
`Uplo` | `int`: Specifies whether matrix A is upper or lower triangular. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`alpha` | `Float2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F32_2`.

### CTRSV

    public void CTRSV (int Uplo,
                    int TransA,
                    int Diag,
                    Allocation A,
                    Allocation X,
                    int incX)

CTRSV solves one of the systems of equations A*x = b or A**T*x = b or A**H*x = b Details: http://www.netlib.org/lapack/explore-html/d4/dc8/ctrsv_8f.html

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### DGBMV

    public void DGBMV (int TransA,
                    int KL,
                    int KU,
                    double alpha,
                    Allocation A,
                    Allocation X,
                    int incX,
                    double beta,
                    Allocation Y,
                    int incY)

DGBMV performs one of the matrix-vector operations y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d2/d3f/dgbmv_8f.html Note: For a M*N matrix, the input Allocation should also be of size M*N (dimY = M, dimX = N), but only the region M*(KL+KU+1) will be referenced. The following subroutine can is an example showing how to convert the original matrix 'a' to row-based band matrix 'b'. for i in range(0, m): for j in range(max(0, i-kl), min(i+ku+1, n)): b[i, j-i+kl] = a[i, j]

Parameters
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`KL` | `int`: The number of sub-diagonals of the matrix A.
`KU` | `int`: The number of super-diagonals of the matrix A.
`alpha` | `double`: The scalar alpha.
`A` | `Allocation`: The input allocation contains the band matrix A, supported elements type `Element#F64`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `double`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F64`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### DGEMM

    public void DGEMM (int TransA,
                    int TransB,
                    double alpha,
                    Allocation A,
                    Allocation B,
                    double beta,
                    Allocation C)

DGEMM performs one of the matrix-matrix operations C := alpha*op(A)*op(B) + beta*C where op(X) is one of op(X) = X or op(X) = X**T Details: http://www.netlib.org/lapack/explore-html/d7/d2b/dgemm_8f.html

Parameters
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`TransB` | `int`: The type of transpose applied to matrix B. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `double`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F64`.
`beta` | `double`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F64`.

### DGEMV

    public void DGEMV (int TransA,
                    double alpha,
                    Allocation A,
                    Allocation X,
                    int incX,
                    double beta,
                    Allocation Y,
                    int incY)

DGEMV performs one of the matrix-vector operations y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y Details: http://www.netlib.org/lapack/explore-html/dc/da8/dgemv_8f.html

Parameters
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `double`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `double`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F64`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### DGER

    public void DGER (double alpha,
                    Allocation X,
                    int incX,
                    Allocation Y,
                    int incY,
                    Allocation A)

DGER performs the rank 1 operation A := alpha*x*y**T + A Details: http://www.netlib.org/lapack/explore-html/dc/da8/dger_8f.html

Parameters
`alpha` | `double`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F64`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.

### DSBMV

    public void DSBMV (int Uplo,
                    int K,
                    double alpha,
                    Allocation A,
                    Allocation X,
                    int incX,
                    double beta,
                    Allocation Y,
                    int incY)

DSBMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d8/d1e/dsbmv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced. The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'. for i in range(0, n): for j in range(i, min(i+k+1, n)): b[i, j-i] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of the band matrix A is being supplied. Value is `UPPER`, or `LOWER`
`K` | `int`: The number of off-diagonals of the matrix A
`alpha` | `double`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `double`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F64`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### DSPMV

    public void DSPMV (int Uplo,
                    double alpha,
                    Allocation Ap,
                    Allocation X,
                    int incX,
                    double beta,
                    Allocation Y,
                    int incY)

DSPMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d4/d85/dspmv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of the matrix A is supplied in packed form. Value is `UPPER`, or `LOWER`
`alpha` | `double`: The scalar alpha.
`Ap` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `double`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F64`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### DSPR

    public void DSPR (int Uplo,
                    double alpha,
                    Allocation X,
                    int incX,
                    Allocation Ap)

DSPR performs the rank 1 operation A := alpha*x*x**T + A Details: http://www.netlib.org/lapack/explore-html/dd/dba/dspr_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be supplied in the packed form. Value is `UPPER`, or `LOWER`
`alpha` | `double`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`Ap` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.

### DSPR2

    public void DSPR2 (int Uplo,
                    double alpha,
                    Allocation X,
                    int incX,
                    Allocation Y,
                    int incY,
                    Allocation Ap)

DSPR2 performs the symmetric rank 2 operation A := alpha*x*y**T + alpha*y*x**T + A Details: http://www.netlib.org/lapack/explore-html/dd/d9e/dspr2_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be supplied in the packed form. Value is `UPPER`, or `LOWER`
`alpha` | `double`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F64`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.
`Ap` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.

### DSYMM

    public void DSYMM (int Side,
                    int Uplo,
                    double alpha,
                    Allocation A,
                    Allocation B,
                    double beta,
                    Allocation C)

DSYMM performs one of the matrix-matrix operations C := alpha*A*B + beta*C or C := alpha*B*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d8/db0/dsymm_8f.html

Parameters
`Side` | `int`: Specifies whether the symmetric matrix A appears on the left or right. Value is `LEFT`, or `RIGHT`
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be referenced. Value is `UPPER`, or `LOWER`
`alpha` | `double`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F64`.
`beta` | `double`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F64`.

### DSYMV

    public void DSYMV (int Uplo,
                    double alpha,
                    Allocation A,
                    Allocation X,
                    int incX,
                    double beta,
                    Allocation Y,
                    int incY)

DSYMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d8/dbe/dsymv_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be referenced. Value is `UPPER`, or `LOWER`
`alpha` | `double`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `double`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F64`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### DSYR

    public void DSYR (int Uplo,
                    double alpha,
                    Allocation X,
                    int incX,
                    Allocation A)

DSYR performs the rank 1 operation A := alpha*x*x**T + A Details: http://www.netlib.org/lapack/explore-html/d3/d60/dsyr_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be referenced. Value is `UPPER`, or `LOWER`
`alpha` | `double`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.

### DSYR2

    public void DSYR2 (int Uplo,
                    double alpha,
                    Allocation X,
                    int incX,
                    Allocation Y,
                    int incY,
                    Allocation A)

DSYR2 performs the symmetric rank 2 operation A := alpha*x*y**T + alpha*y*x**T + A Details: http://www.netlib.org/lapack/explore-html/de/d41/dsyr2_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be referenced. Value is `UPPER`, or `LOWER`
`alpha` | `double`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F64`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.

### DSYR2K

    public void DSYR2K (int Uplo,
                    int Trans,
                    double alpha,
                    Allocation A,
                    Allocation B,
                    double beta,
                    Allocation C)

DSYR2K performs one of the symmetric rank 2k operations C := alpha*A*B**T + alpha*B*A**T + beta*C or C := alpha*A**T*B + alpha*B**T*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d1/dec/dsyr2k_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of C is to be referenced. Value is `UPPER`, or `LOWER`
`Trans` | `int`: The type of transpose applied to the operation. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `double`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F64`.
`beta` | `double`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F64`.

### DSYRK

    public void DSYRK (int Uplo,
                    int Trans,
                    double alpha,
                    Allocation A,
                    double beta,
                    Allocation C)

DSYRK performs one of the symmetric rank k operations C := alpha*A*A**T + beta*C or C := alpha*A**T*A + beta*C Details: http://www.netlib.org/lapack/explore-html/dc/d05/dsyrk_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of C is to be referenced. Value is `UPPER`, or `LOWER`
`Trans` | `int`: The type of transpose applied to the operation. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `double`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.
`beta` | `double`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F64`.

### DTBMV

    public void DTBMV (int Uplo,
                    int TransA,
                    int Diag,
                    int K,
                    Allocation A,
                    Allocation X,
                    int incX)

DTBMV performs one of the matrix-vector operations x := A*x or x := A**T*x Details: http://www.netlib.org/lapack/explore-html/df/d29/dtbmv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced. The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'. for i in range(0, n): for j in range(i, min(i+k+1, n)): b[i, j-i] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`K` | `int`: The number of off-diagonals of the matrix A
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### DTBSV

    public void DTBSV (int Uplo,
                    int TransA,
                    int Diag,
                    int K,
                    Allocation A,
                    Allocation X,
                    int incX)

DTBSV solves one of the systems of equations A*x = b or A**T*x = b Details: http://www.netlib.org/lapack/explore-html/d4/dcf/dtbsv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced. The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'. for i in range(0, n): for j in range(i, min(i+k+1, n)): b[i, j-i] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`K` | `int`: The number of off-diagonals of the matrix A
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### DTPMV

    public void DTPMV (int Uplo,
                    int TransA,
                    int Diag,
                    Allocation Ap,
                    Allocation X,
                    int incX)

DTPMV performs one of the matrix-vector operations x := A*x or x := A**T*x Details: http://www.netlib.org/lapack/explore-html/dc/dcd/dtpmv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`Ap` | `Allocation`: The input allocation contains packed matrix A, supported elements type `Element#F64`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### DTPSV

    public void DTPSV (int Uplo,
                    int TransA,
                    int Diag,
                    Allocation Ap,
                    Allocation X,
                    int incX)

DTPSV solves one of the systems of equations A*x = b or A**T*x = b Details: http://www.netlib.org/lapack/explore-html/d9/d84/dtpsv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`Ap` | `Allocation`: The input allocation contains packed matrix A, supported elements type `Element#F64`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### DTRMM

    public void DTRMM (int Side,
                    int Uplo,
                    int TransA,
                    int Diag,
                    double alpha,
                    Allocation A,
                    Allocation B)

DTRMM performs one of the matrix-matrix operations B := alpha*op(A)*B or B := alpha*B*op(A) op(A) is one of op(A) = A or op(A) = A**T Details: http://www.netlib.org/lapack/explore-html/dd/d19/dtrmm_8f.html

Parameters
`Side` | `int`: Specifies whether the symmetric matrix A appears on the left or right. Value is `LEFT`, or `RIGHT`
`Uplo` | `int`: Specifies whether matrix A is upper or lower triangular. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`alpha` | `double`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F64`.

### DTRMV

    public void DTRMV (int Uplo,
                    int TransA,
                    int Diag,
                    Allocation A,
                    Allocation X,
                    int incX)

DTRMV performs one of the matrix-vector operations x := A*x or x := A**T*x Details: http://www.netlib.org/lapack/explore-html/dc/d7e/dtrmv_8f.html

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### DTRSM

    public void DTRSM (int Side,
                    int Uplo,
                    int TransA,
                    int Diag,
                    double alpha,
                    Allocation A,
                    Allocation B)

DTRSM solves one of the matrix equations op(A)*X := alpha*B or X*op(A) := alpha*B op(A) is one of op(A) = A or op(A) = A**T Details: http://www.netlib.org/lapack/explore-html/de/da7/dtrsm_8f.html

Parameters
`Side` | `int`: Specifies whether the symmetric matrix A appears on the left or right. Value is `LEFT`, or `RIGHT`
`Uplo` | `int`: Specifies whether matrix A is upper or lower triangular. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`alpha` | `double`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F64`.

### DTRSV

    public void DTRSV (int Uplo,
                    int TransA,
                    int Diag,
                    Allocation A,
                    Allocation X,
                    int incX)

DTRSV solves one of the systems of equations A*x = b or A**T*x = b Details: http://www.netlib.org/lapack/explore-html/d6/d96/dtrsv_8f.html

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### SGBMV

    public void SGBMV (int TransA,
                    int KL,
                    int KU,
                    float alpha,
                    Allocation A,
                    Allocation X,
                    int incX,
                    float beta,
                    Allocation Y,
                    int incY)

SGBMV performs one of the matrix-vector operations y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d6/d46/sgbmv_8f.html Note: For a M*N matrix, the input Allocation should also be of size M*N (dimY = M, dimX = N), but only the region M*(KL+KU+1) will be referenced. The following subroutine can is an example showing how to convert the original matrix 'a' to row-based band matrix 'b'. for i in range(0, m): for j in range(max(0, i-kl), min(i+ku+1, n)): b[i, j-i+kl] = a[i, j]

Parameters
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`KL` | `int`: The number of sub-diagonals of the matrix A.
`KU` | `int`: The number of super-diagonals of the matrix A.
`alpha` | `float`: The scalar alpha.
`A` | `Allocation`: The input allocation contains the band matrix A, supported elements type `Element#F32`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `float`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F32`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### SGEMM

    public void SGEMM (int TransA,
                    int TransB,
                    float alpha,
                    Allocation A,
                    Allocation B,
                    float beta,
                    Allocation C)

SGEMM performs one of the matrix-matrix operations C := alpha*op(A)*op(B) + beta*C where op(X) is one of op(X) = X or op(X) = X**T Details: http://www.netlib.org/lapack/explore-html/d4/de2/sgemm_8f.html

Parameters
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`TransB` | `int`: The type of transpose applied to matrix B. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `float`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F32`.
`beta` | `float`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F32`.

### SGEMV

    public void SGEMV (int TransA,
                    float alpha,
                    Allocation A,
                    Allocation X,
                    int incX,
                    float beta,
                    Allocation Y,
                    int incY)

SGEMV performs one of the matrix-vector operations y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y Details: http://www.netlib.org/lapack/explore-html/db/d58/sgemv_8f.html

Parameters
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `float`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `float`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F32`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### SGER

    public void SGER (float alpha,
                    Allocation X,
                    int incX,
                    Allocation Y,
                    int incY,
                    Allocation A)

SGER performs the rank 1 operation A := alpha*x*y**T + A Details: http://www.netlib.org/lapack/explore-html/db/d5c/sger_8f.html

Parameters
`alpha` | `float`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F32`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.

### SSBMV

    public void SSBMV (int Uplo,
                    int K,
                    float alpha,
                    Allocation A,
                    Allocation X,
                    int incX,
                    float beta,
                    Allocation Y,
                    int incY)

SSBMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d3/da1/ssbmv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced. The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'. for i in range(0, n): for j in range(i, min(i+k+1, n)): b[i, j-i] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of the band matrix A is being supplied. Value is `UPPER`, or `LOWER`
`K` | `int`: The number of off-diagonals of the matrix A
`alpha` | `float`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `float`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F32`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### SSPMV

    public void SSPMV (int Uplo,
                    float alpha,
                    Allocation Ap,
                    Allocation X,
                    int incX,
                    float beta,
                    Allocation Y,
                    int incY)

SSPMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d8/d68/sspmv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of the matrix A is supplied in packed form. Value is `UPPER`, or `LOWER`
`alpha` | `float`: The scalar alpha.
`Ap` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `float`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F32`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### SSPR

    public void SSPR (int Uplo,
                    float alpha,
                    Allocation X,
                    int incX,
                    Allocation Ap)

SSPR performs the rank 1 operation A := alpha*x*x**T + A Details: http://www.netlib.org/lapack/explore-html/d2/d9b/sspr_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be supplied in the packed form. Value is `UPPER`, or `LOWER`
`alpha` | `float`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`Ap` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.

### SSPR2

    public void SSPR2 (int Uplo,
                    float alpha,
                    Allocation X,
                    int incX,
                    Allocation Y,
                    int incY,
                    Allocation Ap)

SSPR2 performs the symmetric rank 2 operation A := alpha*x*y**T + alpha*y*x**T + A Details: http://www.netlib.org/lapack/explore-html/db/d3e/sspr2_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be supplied in the packed form. Value is `UPPER`, or `LOWER`
`alpha` | `float`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F32`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.
`Ap` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.

### SSYMM

    public void SSYMM (int Side,
                    int Uplo,
                    float alpha,
                    Allocation A,
                    Allocation B,
                    float beta,
                    Allocation C)

SSYMM performs one of the matrix-matrix operations C := alpha*A*B + beta*C or C := alpha*B*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d7/d42/ssymm_8f.html

Parameters
`Side` | `int`: Specifies whether the symmetric matrix A appears on the left or right. Value is `LEFT`, or `RIGHT`
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be referenced. Value is `UPPER`, or `LOWER`
`alpha` | `float`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F32`.
`beta` | `float`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F32`.

### SSYMV

    public void SSYMV (int Uplo,
                    float alpha,
                    Allocation A,
                    Allocation X,
                    int incX,
                    float beta,
                    Allocation Y,
                    int incY)

SSYMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d2/d94/ssymv_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be referenced. Value is `UPPER`, or `LOWER`
`alpha` | `float`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `float`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F32`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### SSYR

    public void SSYR (int Uplo,
                    float alpha,
                    Allocation X,
                    int incX,
                    Allocation A)

SSYR performs the rank 1 operation A := alpha*x*x**T + A Details: http://www.netlib.org/lapack/explore-html/d6/dac/ssyr_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be referenced. Value is `UPPER`, or `LOWER`
`alpha` | `float`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.

### SSYR2

    public void SSYR2 (int Uplo,
                    float alpha,
                    Allocation X,
                    int incX,
                    Allocation Y,
                    int incY,
                    Allocation A)

SSYR2 performs the symmetric rank 2 operation A := alpha*x*y**T + alpha*y*x**T + A Details: http://www.netlib.org/lapack/explore-html/db/d99/ssyr2_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be referenced. Value is `UPPER`, or `LOWER`
`alpha` | `float`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F32`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.

### SSYR2K

    public void SSYR2K (int Uplo,
                    int Trans,
                    float alpha,
                    Allocation A,
                    Allocation B,
                    float beta,
                    Allocation C)

SSYR2K performs one of the symmetric rank 2k operations C := alpha*A*B**T + alpha*B*A**T + beta*C or C := alpha*A**T*B + alpha*B**T*A + beta*C Details: http://www.netlib.org/lapack/explore-html/df/d3d/ssyr2k_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of C is to be referenced. Value is `UPPER`, or `LOWER`
`Trans` | `int`: The type of transpose applied to the operation. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `float`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F32`.
`beta` | `float`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F32`.

### SSYRK

    public void SSYRK (int Uplo,
                    int Trans,
                    float alpha,
                    Allocation A,
                    float beta,
                    Allocation C)

SSYRK performs one of the symmetric rank k operations C := alpha*A*A**T + beta*C or C := alpha*A**T*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d0/d40/ssyrk_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of C is to be referenced. Value is `UPPER`, or `LOWER`
`Trans` | `int`: The type of transpose applied to the operation. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `float`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.
`beta` | `float`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F32`.

### STBMV

    public void STBMV (int Uplo,
                    int TransA,
                    int Diag,
                    int K,
                    Allocation A,
                    Allocation X,
                    int incX)

STBMV performs one of the matrix-vector operations x := A*x or x := A**T*x Details: http://www.netlib.org/lapack/explore-html/d6/d7d/stbmv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced. The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'. for i in range(0, n): for j in range(i, min(i+k+1, n)): b[i, j-i] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`K` | `int`: The number of off-diagonals of the matrix A
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### STBSV

    public void STBSV (int Uplo,
                    int TransA,
                    int Diag,
                    int K,
                    Allocation A,
                    Allocation X,
                    int incX)

STBSV solves one of the systems of equations A*x = b or A**T*x = b Details: http://www.netlib.org/lapack/explore-html/d0/d1f/stbsv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced. The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'. for i in range(0, n): for j in range(i, min(i+k+1, n)): b[i, j-i] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`K` | `int`: The number of off-diagonals of the matrix A
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### STPMV

    public void STPMV (int Uplo,
                    int TransA,
                    int Diag,
                    Allocation Ap,
                    Allocation X,
                    int incX)

STPMV performs one of the matrix-vector operations x := A*x or x := A**T*x Details: http://www.netlib.org/lapack/explore-html/db/db1/stpmv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`Ap` | `Allocation`: The input allocation contains packed matrix A, supported elements type `Element#F32`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### STPSV

    public void STPSV (int Uplo,
                    int TransA,
                    int Diag,
                    Allocation Ap,
                    Allocation X,
                    int incX)

STPSV solves one of the systems of equations A*x = b or A**T*x = b Details: http://www.netlib.org/lapack/explore-html/d0/d7c/stpsv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`Ap` | `Allocation`: The input allocation contains packed matrix A, supported elements type `Element#F32`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### STRMM

    public void STRMM (int Side,
                    int Uplo,
                    int TransA,
                    int Diag,
                    float alpha,
                    Allocation A,
                    Allocation B)

STRMM performs one of the matrix-matrix operations B := alpha*op(A)*B or B := alpha*B*op(A) op(A) is one of op(A) = A or op(A) = A**T Details: http://www.netlib.org/lapack/explore-html/df/d01/strmm_8f.html

Parameters
`Side` | `int`: Specifies whether the symmetric matrix A appears on the left or right. Value is `LEFT`, or `RIGHT`
`Uplo` | `int`: Specifies whether matrix A is upper or lower triangular. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`alpha` | `float`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F32`.

### STRMV

    public void STRMV (int Uplo,
                    int TransA,
                    int Diag,
                    Allocation A,
                    Allocation X,
                    int incX)

STRMV performs one of the matrix-vector operations x := A*x or x := A**T*x Details: http://www.netlib.org/lapack/explore-html/de/d45/strmv_8f.html

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### STRSM

    public void STRSM (int Side,
                    int Uplo,
                    int TransA,
                    int Diag,
                    float alpha,
                    Allocation A,
                    Allocation B)

STRSM solves one of the matrix equations op(A)*X := alpha*B or X*op(A) := alpha*B op(A) is one of op(A) = A or op(A) = A**T Details: http://www.netlib.org/lapack/explore-html/d2/d8b/strsm_8f.html

Parameters
`Side` | `int`: Specifies whether the symmetric matrix A appears on the left or right. Value is `LEFT`, or `RIGHT`
`Uplo` | `int`: Specifies whether matrix A is upper or lower triangular. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`alpha` | `float`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F32`.

### STRSV

    public void STRSV (int Uplo,
                    int TransA,
                    int Diag,
                    Allocation A,
                    Allocation X,
                    int incX)

STRSV solves one of the systems of equations A*x = b or A**T*x = b Details: http://www.netlib.org/lapack/explore-html/d0/d2a/strsv_8f.html

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F32`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F32`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### ZGBMV

    public void ZGBMV (int TransA,
                    int KL,
                    int KU,
                    Double2 alpha,
                    Allocation A,
                    Allocation X,
                    int incX,
                    Double2 beta,
                    Allocation Y,
                    int incY)

ZGBMV performs one of the matrix-vector operations y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y or y := alpha*A**H*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d9/d46/zgbmv_8f.html Note: For a M*N matrix, the input Allocation should also be of size M*N (dimY = M, dimX = N), but only the region M*(KL+KU+1) will be referenced. The following subroutine can is an example showing how to convert the original matrix 'a' to row-based band matrix 'b'. for i in range(0, m): for j in range(max(0, i-kl), min(i+ku+1, n)): b[i, j-i+kl] = a[i, j]

Parameters
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`KL` | `int`: The number of sub-diagonals of the matrix A.
`KU` | `int`: The number of super-diagonals of the matrix A.
`alpha` | `Double2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains the band matrix A, supported elements type `Element#F64_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `Double2`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F64_2`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### ZGEMM

    public void ZGEMM (int TransA,
                    int TransB,
                    Double2 alpha,
                    Allocation A,
                    Allocation B,
                    Double2 beta,
                    Allocation C)

ZGEMM performs one of the matrix-matrix operations C := alpha*op(A)*op(B) + beta*C where op(X) is one of op(X) = X or op(X) = X**T or op(X) = X**H Details: http://www.netlib.org/lapack/explore-html/d7/d76/zgemm_8f.html

Parameters
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`TransB` | `int`: The type of transpose applied to matrix B. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `Double2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F64_2`.
`beta` | `Double2`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F64_2`.

### ZGEMV

    public void ZGEMV (int TransA,
                    Double2 alpha,
                    Allocation A,
                    Allocation X,
                    int incX,
                    Double2 beta,
                    Allocation Y,
                    int incY)

ZGEMV performs one of the matrix-vector operations y := alpha*A*x + beta*y or y := alpha*A**T*x + beta*y or y := alpha*A**H*x + beta*y Details: http://www.netlib.org/lapack/explore-html/db/d40/zgemv_8f.html

Parameters
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `Double2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `Double2`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F64_2`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### ZGERC

    public void ZGERC (Double2 alpha,
                    Allocation X,
                    int incX,
                    Allocation Y,
                    int incY,
                    Allocation A)

ZGERC performs the rank 1 operation A := alpha*x*y**H + A Details: http://www.netlib.org/lapack/explore-html/d3/dad/zgerc_8f.html

Parameters
`alpha` | `Double2`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F64_2`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.

### ZGERU

    public void ZGERU (Double2 alpha,
                    Allocation X,
                    int incX,
                    Allocation Y,
                    int incY,
                    Allocation A)

ZGERU performs the rank 1 operation A := alpha*x*y**T + A Details: http://www.netlib.org/lapack/explore-html/d7/d12/zgeru_8f.html

Parameters
`alpha` | `Double2`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F64_2`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.

### ZHBMV

    public void ZHBMV (int Uplo,
                    int K,
                    Double2 alpha,
                    Allocation A,
                    Allocation X,
                    int incX,
                    Double2 beta,
                    Allocation Y,
                    int incY)

ZHBMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d3/d1a/zhbmv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced. The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'. for i in range(0, n): for j in range(i, min(i+k+1, n)): b[i, j-i] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of the band matrix A is being supplied. Value is `UPPER`, or `LOWER`
`K` | `int`: The number of off-diagonals of the matrix A
`alpha` | `Double2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `Double2`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F64_2`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### ZHEMM

    public void ZHEMM (int Side,
                    int Uplo,
                    Double2 alpha,
                    Allocation A,
                    Allocation B,
                    Double2 beta,
                    Allocation C)

ZHEMM performs one of the matrix-matrix operations C := alpha*A*B + beta*C or C := alpha*B*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d6/d3e/zhemm_8f.html

Parameters
`Side` | `int`: Specifies whether the symmetric matrix A appears on the left or right. Value is `LEFT`, or `RIGHT`
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be referenced. Value is `UPPER`, or `LOWER`
`alpha` | `Double2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F64_2`.
`beta` | `Double2`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F64_2`.

### ZHEMV

    public void ZHEMV (int Uplo,
                    Double2 alpha,
                    Allocation A,
                    Allocation X,
                    int incX,
                    Double2 beta,
                    Allocation Y,
                    int incY)

ZHEMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d0/ddd/zhemv_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be referenced. Value is `UPPER`, or `LOWER`
`alpha` | `Double2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `Double2`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F64_2`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### ZHER

    public void ZHER (int Uplo,
                    double alpha,
                    Allocation X,
                    int incX,
                    Allocation A)

ZHER performs the rank 1 operation A := alpha*x*x**H + A Details: http://www.netlib.org/lapack/explore-html/de/d0e/zher_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be referenced. Value is `UPPER`, or `LOWER`
`alpha` | `double`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.

### ZHER2

    public void ZHER2 (int Uplo,
                    Double2 alpha,
                    Allocation X,
                    int incX,
                    Allocation Y,
                    int incY,
                    Allocation A)

ZHER2 performs the symmetric rank 2 operation A := alpha*x*y**H + alpha*y*x**H + A Details: http://www.netlib.org/lapack/explore-html/da/d8a/zher2_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be referenced. Value is `UPPER`, or `LOWER`
`alpha` | `Double2`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F64_2`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.

### ZHER2K

    public void ZHER2K (int Uplo,
                    int Trans,
                    Double2 alpha,
                    Allocation A,
                    Allocation B,
                    double beta,
                    Allocation C)

ZHER2K performs one of the hermitian rank 2k operations C := alpha*A*B**H + conjg( alpha )*B*A**H + beta*C or C := alpha*A**H*B + conjg( alpha )*B**H*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d7/dfa/zher2k_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of C is to be referenced. Value is `UPPER`, or `LOWER`
`Trans` | `int`: The type of transpose applied to the operation. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `Double2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F64_2`.
`beta` | `double`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F64_2`.

### ZHERK

    public void ZHERK (int Uplo,
                    int Trans,
                    double alpha,
                    Allocation A,
                    double beta,
                    Allocation C)

ZHERK performs one of the hermitian rank k operations C := alpha*A*A**H + beta*C or C := alpha*A**H*A + beta*C Details: http://www.netlib.org/lapack/explore-html/d1/db1/zherk_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of C is to be referenced. Value is `UPPER`, or `LOWER`
`Trans` | `int`: The type of transpose applied to the operation. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `double`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.
`beta` | `double`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F64_2`.

### ZHPMV

    public void ZHPMV (int Uplo,
                    Double2 alpha,
                    Allocation Ap,
                    Allocation X,
                    int incX,
                    Double2 beta,
                    Allocation Y,
                    int incY)

ZHPMV performs the matrix-vector operation y := alpha*A*x + beta*y Details: http://www.netlib.org/lapack/explore-html/d0/d60/zhpmv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of the matrix A is supplied in packed form. Value is `UPPER`, or `LOWER`
`alpha` | `Double2`: The scalar alpha.
`Ap` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`beta` | `Double2`: The scalar beta.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F64_2`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.

### ZHPR

    public void ZHPR (int Uplo,
                    double alpha,
                    Allocation X,
                    int incX,
                    Allocation Ap)

ZHPR performs the rank 1 operation A := alpha*x*x**H + A Details: http://www.netlib.org/lapack/explore-html/de/de1/zhpr_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be supplied in the packed form. Value is `UPPER`, or `LOWER`
`alpha` | `double`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`Ap` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.

### ZHPR2

    public void ZHPR2 (int Uplo,
                    Double2 alpha,
                    Allocation X,
                    int incX,
                    Allocation Y,
                    int incY,
                    Allocation Ap)

ZHPR2 performs the symmetric rank 2 operation A := alpha*x*y**H + alpha*y*x**H + A Details: http://www.netlib.org/lapack/explore-html/d5/d52/zhpr2_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be supplied in the packed form. Value is `UPPER`, or `LOWER`
`alpha` | `Double2`: The scalar alpha.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.
`Y` | `Allocation`: The input allocation contains vector y, supported elements type `Element#F64_2`.
`incY` | `int`: The increment for the elements of vector y, must be larger than zero.
`Ap` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.

### ZSYMM

    public void ZSYMM (int Side,
                    int Uplo,
                    Double2 alpha,
                    Allocation A,
                    Allocation B,
                    Double2 beta,
                    Allocation C)

ZSYMM performs one of the matrix-matrix operations C := alpha*A*B + beta*C or C := alpha*B*A + beta*C Details: http://www.netlib.org/lapack/explore-html/df/d51/zsymm_8f.html

Parameters
`Side` | `int`: Specifies whether the symmetric matrix A appears on the left or right. Value is `LEFT`, or `RIGHT`
`Uplo` | `int`: Specifies whether the upper or lower triangular part is to be referenced. Value is `UPPER`, or `LOWER`
`alpha` | `Double2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F64_2`.
`beta` | `Double2`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F64_2`.

### ZSYR2K

    public void ZSYR2K (int Uplo,
                    int Trans,
                    Double2 alpha,
                    Allocation A,
                    Allocation B,
                    Double2 beta,
                    Allocation C)

ZSYR2K performs one of the symmetric rank 2k operations C := alpha*A*B**T + alpha*B*A**T + beta*C or C := alpha*A**T*B + alpha*B**T*A + beta*C Details: http://www.netlib.org/lapack/explore-html/df/d20/zsyr2k_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of C is to be referenced. Value is `UPPER`, or `LOWER`
`Trans` | `int`: The type of transpose applied to the operation. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `Double2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F64_2`.
`beta` | `Double2`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F64_2`.

### ZSYRK

    public void ZSYRK (int Uplo,
                    int Trans,
                    Double2 alpha,
                    Allocation A,
                    Double2 beta,
                    Allocation C)

ZSYRK performs one of the symmetric rank k operations C := alpha*A*A**T + beta*C or C := alpha*A**T*A + beta*C Details: http://www.netlib.org/lapack/explore-html/de/d54/zsyrk_8f.html

Parameters
`Uplo` | `int`: Specifies whether the upper or lower triangular part of C is to be referenced. Value is `UPPER`, or `LOWER`
`Trans` | `int`: The type of transpose applied to the operation. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`alpha` | `Double2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.
`beta` | `Double2`: The scalar beta.
`C` | `Allocation`: The input allocation contains matrix C, supported elements type `Element#F64_2`.

### ZTBMV

    public void ZTBMV (int Uplo,
                    int TransA,
                    int Diag,
                    int K,
                    Allocation A,
                    Allocation X,
                    int incX)

ZTBMV performs one of the matrix-vector operations x := A*x or x := A**T*x or x := A**H*x Details: http://www.netlib.org/lapack/explore-html/d3/d39/ztbmv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced. The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'. for i in range(0, n): for j in range(i, min(i+k+1, n)): b[i, j-i] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`K` | `int`: The number of off-diagonals of the matrix A
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### ZTBSV

    public void ZTBSV (int Uplo,
                    int TransA,
                    int Diag,
                    int K,
                    Allocation A,
                    Allocation X,
                    int incX)

ZTBSV solves one of the systems of equations A*x = b or A**T*x = b or A**H*x = b Details: http://www.netlib.org/lapack/explore-html/d4/d5a/ztbsv_8f.html Note: For a N*N matrix, the input Allocation should also be of size N*N (dimY = N, dimX = N), but only the region N*(K+1) will be referenced. The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to row-based band matrix 'b'. for i in range(0, n): for j in range(i, min(i+k+1, n)): b[i, j-i] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`K` | `int`: The number of off-diagonals of the matrix A
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### ZTPMV

    public void ZTPMV (int Uplo,
                    int TransA,
                    int Diag,
                    Allocation Ap,
                    Allocation X,
                    int incX)

ZTPMV performs one of the matrix-vector operations x := A*x or x := A**T*x or x := A**H*x Details: http://www.netlib.org/lapack/explore-html/d2/d9e/ztpmv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`Ap` | `Allocation`: The input allocation contains packed matrix A, supported elements type `Element#F64_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### ZTPSV

    public void ZTPSV (int Uplo,
                    int TransA,
                    int Diag,
                    Allocation Ap,
                    Allocation X,
                    int incX)

ZTPSV solves one of the systems of equations A*x = b or A**T*x = b or A**H*x = b Details: http://www.netlib.org/lapack/explore-html/da/d57/ztpsv_8f.html Note: For a N*N matrix, the input Allocation should be a 1D allocation of size dimX = N*(N+1)/2, The following subroutine can is an example showing how to convert a UPPER trianglar matrix 'a' to packed matrix 'b'. k = 0 for i in range(0, n): for j in range(i, n): b[k++] = a[i, j]

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`Ap` | `Allocation`: The input allocation contains packed matrix A, supported elements type `Element#F64_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### ZTRMM

    public void ZTRMM (int Side,
                    int Uplo,
                    int TransA,
                    int Diag,
                    Double2 alpha,
                    Allocation A,
                    Allocation B)

ZTRMM performs one of the matrix-matrix operations B := alpha*op(A)*B or B := alpha*B*op(A) op(A) is one of op(A) = A or op(A) = A**T or op(A) = A**H Details: http://www.netlib.org/lapack/explore-html/d8/de1/ztrmm_8f.html

Parameters
`Side` | `int`: Specifies whether the symmetric matrix A appears on the left or right. Value is `LEFT`, or `RIGHT`
`Uplo` | `int`: Specifies whether matrix A is upper or lower triangular. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`alpha` | `Double2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F64_2`.

### ZTRMV

    public void ZTRMV (int Uplo,
                    int TransA,
                    int Diag,
                    Allocation A,
                    Allocation X,
                    int incX)

ZTRMV performs one of the matrix-vector operations x := A*x or x := A**T*x or x := A**H*x Details: http://www.netlib.org/lapack/explore-html/d0/dd1/ztrmv_8f.html

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### ZTRSM

    public void ZTRSM (int Side,
                    int Uplo,
                    int TransA,
                    int Diag,
                    Double2 alpha,
                    Allocation A,
                    Allocation B)

ZTRSM solves one of the matrix equations op(A)*X := alpha*B or X*op(A) := alpha*B op(A) is one of op(A) = A or op(A) = A**T or op(A) = A**H Details: http://www.netlib.org/lapack/explore-html/d1/d39/ztrsm_8f.html

Parameters
`Side` | `int`: Specifies whether the symmetric matrix A appears on the left or right. Value is `LEFT`, or `RIGHT`
`Uplo` | `int`: Specifies whether matrix A is upper or lower triangular. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`alpha` | `Double2`: The scalar alpha.
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.
`B` | `Allocation`: The input allocation contains matrix B, supported elements type `Element#F64_2`.

### ZTRSV

    public void ZTRSV (int Uplo,
                    int TransA,
                    int Diag,
                    Allocation A,
                    Allocation X,
                    int incX)

ZTRSV solves one of the systems of equations A*x = b or A**T*x = b or A**H*x = b Details: http://www.netlib.org/lapack/explore-html/d1/d2f/ztrsv_8f.html

Parameters
`Uplo` | `int`: Specifies whether the matrix is an upper or lower triangular matrix. Value is `UPPER`, or `LOWER`
`TransA` | `int`: The type of transpose applied to matrix A. Value is `NO_TRANSPOSE`, `TRANSPOSE`, or `CONJ_TRANSPOSE`
`Diag` | `int`: Specifies whether or not A is unit triangular. Value is `NON_UNIT`, or `UNIT`
`A` | `Allocation`: The input allocation contains matrix A, supported elements type `Element#F64_2`.
`X` | `Allocation`: The input allocation contains vector x, supported elements type `Element#F64_2`.
`incX` | `int`: The increment for the elements of vector x, must be larger than zero.

### create

    public static ScriptIntrinsicBLAS create (RenderScript rs)

Create an intrinsic to access BLAS subroutines.

Parameters
`rs` | `RenderScript`: The RenderScript context

Returns
`ScriptIntrinsicBLAS` | ScriptIntrinsicBLAS

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