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cuBLAS使用(3)

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2025-05-29 07:44:10

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cublasgbmv()

cublasspr()

cublasspr2()

cublasspmv()

cublasspr()

cublasgemvStridedBatched()

cublasgemvBatched()

cublashpr()

cublasher2()

cublashpmv()

cublashbmv()

cublashemv()

cublastrsv()

cublastrmv()

cublastpsv()

cublastpmv()

cublastbsv()

cublastbmv()

cublassyr2()

cublassyr()

cublassymv()

cublassbmv()

cublasger()

cublasgemv()

在本章中，我们将介绍执行矩阵-向量运算的二级基本线性代数子程序（BLAS2）函数。

cublasgbmv()

cublasStatus_t cublasSgbmv(cublasHandle_t handle, cublasOperation_t trans,int m, int n, int kl, int ku,const float           *alpha,const float           *A, int lda,const float           *x, int incx,const float           *beta,float           *y, int incy)
cublasStatus_t cublasDgbmv(cublasHandle_t handle, cublasOperation_t trans,int m, int n, int kl, int ku,const double          *alpha,const double          *A, int lda,const double          *x, int incx,const double          *beta,double          *y, int incy)
cublasStatus_t cublasCgbmv(cublasHandle_t handle, cublasOperation_t trans,int m, int n, int kl, int ku,const cuComplex       *alpha,const cuComplex       *A, int lda,const cuComplex       *x, int incx,const cuComplex       *beta,cuComplex       *y, int incy)
cublasStatus_t cublasZgbmv(cublasHandle_t handle, cublasOperation_t trans,int m, int n, int kl, int ku,const cuDoubleComplex *alpha,const cuDoubleComplex *A, int lda,const cuDoubleComplex *x, int incx,const cuDoubleComplex *beta,cuDoubleComplex *y, int incy)

此函数支持64位整数接口。
此函数执行带状矩阵向量乘法

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix � lower or upper part is stored, the other symmetric part is not referenced and is inferred from the stored elements.
n		input	number of rows and columns of matrix � .
alpha	host or device	input	scalar used for multiplication.
AP	device	input	array with � stored in packed format.
x	device	input	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.
beta	host or device	input	scalar used for multiplication, if `beta==0` then `y` does not have to be a valid input.
y	device	input	vector with `n` elements.
incy		input	stride between consecutive elements of `y`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or if `incx` = 0 or `incy` = 0 or if `uplo` != `CUBLAS_FILL_MODE_LOWER`, `CUBLAS_FILL_MODE_UPPER` or `alpha` == NULL or `beta` == NULL
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublasspr()

cublasStatus_t cublasSspr(cublasHandle_t handle, cublasFillMode_t uplo,int n, const float  *alpha,const float  *x, int incx, float  *AP)
cublasStatus_t cublasDspr(cublasHandle_t handle, cublasFillMode_t uplo,int n, const double *alpha,const double *x, int incx, double *AP)

此函数支持64位整数接口。
此函数执行压缩对称秩1更新

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix � lower or upper part is stored, the other symmetric part is not referenced and is inferred from the stored elements.
n		input	number of rows and columns of matrix � .
alpha	host or device	input	scalar used for multiplication.
x	device	input	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.
AP	device	in/out	array with � stored in packed format.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or if `incx` = 0 or if `uplo` != `CUBLAS_FILL_MODE_LOWER`, `CUBLAS_FILL_MODE_UPPER` or `alpha` == NULL
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublasspr2()

cublasStatus_t cublasSspr2(cublasHandle_t handle, cublasFillMode_t uplo,int n, const float  *alpha,const float  *x, int incx,const float  *y, int incy, float  *AP)
cublasStatus_t cublasDspr2(cublasHandle_t handle, cublasFillMode_t uplo,int n, const double *alpha,const double *x, int incx,const double *y, int incy, double *AP)

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix � lower or upper part is stored, the other symmetric part is not referenced and is inferred from the stored elements.
n		input	number of rows and columns of matrix � .
alpha	host or device	input	scalar used for multiplication.
x	device	input	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.
y	device	input	vector with `n` elements.
incy		input	stride between consecutive elements of `y`.
AP	device	in/out	array with � stored in packed format.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or if `incx` = 0 or `incy` = 0 or if `uplo` != `CUBLAS_FILL_MODE_LOWER`, `CUBLAS_FILL_MODE_UPPER` or `alpha` == NULL
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublassbmv()

cublasStatus_t cublasSsbmv(cublasHandle_t handle, cublasFillMode_t uplo,int n, int k, const float  *alpha,const float  *A, int lda,const float  *x, int incx,const float  *beta, float *y, int incy)
cublasStatus_t cublasDsbmv(cublasHandle_t handle, cublasFillMode_t uplo,int n, int k, const double *alpha,const double *A, int lda,const double *x, int incx,const double *beta, double *y, int incy)

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix `A` lower or upper part is stored, the other symmetric part is not referenced and is inferred from the stored elements.
n		input	number of rows and columns of matrix `A`.
k		input	number of sub- and super-diagonals of matrix `A`.
alpha	host or device	input	scalar used for multiplication.
A	device	input	array of dimension `lda x n` with `\lda >= k+1`.
lda		input	leading dimension of two-dimensional array used to store matrix `A`.
x	device	input	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.
beta	host or device	input	scalar used for multiplication, if `beta==0` then `y` does not have to be a valid input.
y	device	in/out	vector with `n` elements.
incy		input	stride between consecutive elements of `y`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or `k` < 0 or if `incx` = 0 or `incy` = 0 or if `uplo` != `CUBLAS_FILL_MODE_LOWER`, `CUBLAS_FILL_MODE_UPPER` or if `alpha` == NULL or `beta` == NULL or `lda` < (1 + `k`)
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublasspmv()

cublasStatus_t cublasSspmv(cublasHandle_t handle, cublasFillMode_t uplo,int n, const float  *alpha, const float  *AP,const float  *x, int incx, const float  *beta,float  *y, int incy)
cublasStatus_t cublasDspmv(cublasHandle_t handle, cublasFillMode_t uplo,int n, const double *alpha, const double *AP,const double *x, int incx, const double *beta,double *y, int incy)

此函数支持64位整数接口。
此函数执行对称压缩矩阵-向量乘法

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix � lower or upper part is stored, the other symmetric part is not referenced and is inferred from the stored elements.
n		input	number of rows and columns of matrix � .
alpha	host or device	input	scalar used for multiplication.
AP	device	input	array with � stored in packed format.
x	device	input	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.
beta	host or device	input	scalar used for multiplication, if `beta==0` then `y` does not have to be a valid input.
y	device	input	vector with `n` elements.
incy		input	stride between consecutive elements of `y`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or if `incx` = 0 or `incy` = 0 or if `uplo` != `CUBLAS_FILL_MODE_LOWER`, `CUBLAS_FILL_MODE_UPPER` or `alpha` == NULL or `beta` == NULL
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublasspr()

cublasStatus_t cublasSspr(cublasHandle_t handle, cublasFillMode_t uplo,int n, const float  *alpha,const float  *x, int incx, float  *AP)
cublasStatus_t cublasDspr(cublasHandle_t handle, cublasFillMode_t uplo,int n, const double *alpha,const double *x, int incx, double *AP)

此函数支持64位整数接口。
此函数执行压缩对称秩1更新

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix � lower or upper part is stored, the other symmetric part is not referenced and is inferred from the stored elements.
n		input	number of rows and columns of matrix � .
alpha	host or device	input	scalar used for multiplication.
x	device	input	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.
AP	device	in/out	array with � stored in packed format.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or if `incx` = 0 or if `uplo` != `CUBLAS_FILL_MODE_LOWER`, `CUBLAS_FILL_MODE_UPPER` or `alpha` == NULL
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublasgemvStridedBatched()

cublasStatus_t cublasSgemvStridedBatched(cublasHandle_t handle,cublasOperation_t trans,int m, int n,const float           *alpha,const float           *A, int lda,long long int         strideA,const float           *x, int incx,long long int         stridex,const float           *beta,float                 *y, int incy,long long int         stridey,int batchCount)
cublasStatus_t cublasDgemvStridedBatched(cublasHandle_t handle,cublasOperation_t trans,int m, int n,const double          *alpha,const double          *A, int lda,long long int         strideA,const double          *x, int incx,long long int         stridex,const double          *beta,double                *yarray[], int incy,long long int         stridey,int batchCount)
cublasStatus_t cublasCgemvStridedBatched(cublasHandle_t handle,cublasOperation_t trans,int m, int n,const cuComplex       *alpha,const cuComplex       *A, int lda,long long int         strideA,const cuComplex       *x, int incx,long long int         stridex,const cuComplex       *beta,cuComplex             *y, int incy,long long int         stridey,int batchCount)
cublasStatus_t cublasZgemvStridedBatched(cublasHandle_t handle,cublasOperation_t trans,int m, int n,const cuDoubleComplex *alpha,const cuDoubleComplex *A, int lda,long long int         strideA,const cuDoubleComplex *x, int incx,long long int         stridex,const cuDoubleComplex *beta,cuDoubleComplex       *y, int incy,long long int         stridey,int batchCount)
cublasStatus_t cublasHSHgemvStridedBatched(cublasHandle_t handle,cublasOperation_t trans,int m, int n,const float           *alpha,const __half          *A, int lda,long long int         strideA,const __half          *x, int incx,long long int         stridex,const float           *beta,__half                *y, int incy,long long int         stridey,int batchCount)
cublasStatus_t cublasHSSgemvStridedBatched(cublasHandle_t handle,cublasOperation_t trans,int m, int n,const float           *alpha,const __half          *A, int lda,long long int         strideA,const __half          *x, int incx,long long int         stridex,const float           *beta,float                 *y, int incy,long long int         stridey,int batchCount)
cublasStatus_t cublasTSTgemvStridedBatched(cublasHandle_t handle,cublasOperation_t trans,int m, int n,const float           *alpha,const __nv_bfloat16   *A, int lda,long long int         strideA,const __nv_bfloat16   *x, int incx,long long int         stridex,const float           *beta,__nv_bfloat16         *y, int incy,long long int         stridey,int batchCount)
cublasStatus_t cublasTSSgemvStridedBatched(cublasHandle_t handle,cublasOperation_t trans,int m, int n,const float           *alpha,const __nv_bfloat16   *A, int lda,long long int         strideA,const __nv_bfloat16   *x, int incx,long long int         stridex,const float           *beta,float                 *y, int incy,long long int         stridey,int batchCount)

此函数支持64位整数接口。
此函数执行一批矩阵和向量的矩阵向量乘法。该批被认为是“均匀的，”即所有实例对于它们各自的A矩阵、x和y向量具有相同的维数（m，n）、前导维数（lda）、增量（incx，incy）和转置（trans）.批处理的每个实例的输入矩阵A和向量x以及输出向量y位于相对于它们在前一实例中的位置的固定元素偏移量处。指向A矩阵的指针、第一个实例的x和y向量以及元素数量的偏移量（strideA、stridex和stridey）由用户传递给函数，这些元素确定输入矩阵和向量的位置，以及未来实例中的输出向量。

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
trans		input	operation op(`A[i]`) that is non- or (conj.) transpose.
m		input	number of rows of matrix `A[i]`.
n		input	number of columns of matrix `A[i]`.
alpha	host or device	input	scalar used for multiplication.
A	device	input	* pointer to the A matrix corresponding to the first instance of the batch, with dimensions `lda x n` with `lda>=max(1,m)`.
lda		input	leading dimension of two-dimensional array used to store each matrix `A[i]`.
strideA		input	Value of type long long int that gives the offset in number of elements between `A[i]` and `A[i+1]`
x	device	input	* pointer to the x vector corresponding to the first instance of the batch, with each dimension `n` if `trans==CUBLAS_OP_N` and `m` otherwise.
incx		input	stride of each one-dimensional array x[i].
stridex		input	Value of type long long int that gives the offset in number of elements between `x[i]` and `x[i+1]`
beta	host or device	input	scalar used for multiplication. If `beta == 0`, `y` does not have to be a valid input.
y	device	in/out	* pointer to the y vector corresponding to the first instance of the batch, with each dimension `m` if `trans==CUBLAS_OP_N` and `n` otherwise. Vectors `y[i]` should not overlap; otherwise, undefined behavior is expected.
incy		input	stride of each one-dimensional array y[i].
stridey		input	Value of type long long int that gives the offset in number of elements between `y[i]` and `y[i+1]`
batchCount		input	number of GEMVs to perform in the batch.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	the parameters `m,n,batchCount<0`
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublasgemvBatched()

cublasStatus_t cublasSgemvBatched(cublasHandle_t handle, cublasOperation_t trans,int m, int n,const float           *alpha,const float           *Aarray[], int lda,const float           *xarray[], int incx,const float           *beta,float           *yarray[], int incy,int batchCount)
cublasStatus_t cublasDgemvBatched(cublasHandle_t handle, cublasOperation_t trans,int m, int n,const double          *alpha,const double          *Aarray[], int lda,const double          *xarray[], int incx,const double          *beta,double          *yarray[], int incy,int batchCount)
cublasStatus_t cublasCgemvBatched(cublasHandle_t handle, cublasOperation_t trans,int m, int n,const cuComplex       *alpha,const cuComplex       *Aarray[], int lda,const cuComplex       *xarray[], int incx,const cuComplex       *beta,cuComplex       *yarray[], int incy,int batchCount)
cublasStatus_t cublasZgemvBatched(cublasHandle_t handle, cublasOperation_t trans,int m, int n,const cuDoubleComplex *alpha,const cuDoubleComplex *Aarray[], int lda,const cuDoubleComplex *xarray[], int incx,const cuDoubleComplex *beta,cuDoubleComplex *yarray[], int incy,int batchCount)
cublasStatus_t cublasHSHgemvBatched(cublasHandle_t handle, cublasOperation_t trans,int m, int n,const float           *alpha,const __half          *Aarray[], int lda,const __half          *xarray[], int incx,const float           *beta,__half                *yarray[], int incy,int batchCount)
cublasStatus_t cublasHSSgemvBatched(cublasHandle_t handle, cublasOperation_t trans,int m, int n,const float           *alpha,const __half          *Aarray[], int lda,const __half          *xarray[], int incx,const float           *beta,float                 *yarray[], int incy,int batchCount)
cublasStatus_t cublasTSTgemvBatched(cublasHandle_t handle, cublasOperation_t trans,int m, int n,const float           *alpha,const __nv_bfloat16   *Aarray[], int lda,const __nv_bfloat16   *xarray[], int incx,const float           *beta,__nv_bfloat16         *yarray[], int incy,int batchCount)
cublasStatus_t cublasTSSgemvBatched(cublasHandle_t handle, cublasOperation_t trans,int m, int n,const float           *alpha,const __nv_bfloat16   *Aarray[], int lda,const __nv_bfloat16   *xarray[], int incx,const float           *beta,float                 *yarray[], int incy,int batchCount)

此函数支持64位整数接口。
此函数执行一批矩阵和向量的矩阵向量乘法。该批被认为是“均匀的，”即所有实例对于它们各自的A矩阵、x和y向量具有相同的维数（m，n）、前导维数（lda）、增量（incx，incy）和转置（trans）.输入矩阵和向量的地址以及批处理的每个实例的输出向量是从调用方传递给函数的指针数组中读取的。

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
trans		input	operation op(`A[i]`) that is non- or (conj.) transpose.
m		input	number of rows of matrix `A[i]`.
n		input	number of columns of matrix `A[i]`.
alpha	host or device	input	scalar used for multiplication.
Aarray	device	input	array of pointers to array, with each array of dim. `lda x n` with `lda>=max(1,m)`. All pointers must meet certain alignment criteria. Please see below for details.
lda		input	leading dimension of two-dimensional array used to store each matrix `A[i]`.
xarray	device	input	array of pointers to array, with each dimension `n` if `trans==CUBLAS_OP_N` and `m` otherwise. All pointers must meet certain alignment criteria. Please see below for details.
incx		input	stride of each one-dimensional array x[i].
beta	host or device	input	scalar used for multiplication. If `beta == 0`, `y` does not have to be a valid input.
yarray	device	in/out	array of pointers to array. It has dimensions `m` if `trans==CUBLAS_OP_N` and `n` otherwise. Vectors `y[i]` should not overlap; otherwise, undefined behavior is expected. All pointers must meet certain alignment criteria. Please see below for details.
incy		input	stride of each one-dimensional array y[i].
batchCount		input	number of pointers contained in Aarray, xarray and yarray.

If math mode enables fast math modes when using cublasSgemvBatched(), pointers (not the pointer arrays) placed in the GPU memory must be properly aligned to avoid misaligned memory access errors. Ideally all pointers are aligned to at least 16 Bytes. Otherwise it is recommended that they meet the following rule:

if k % 4==0 then ensure intptr_t(ptr) % 16 == 0,

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	the parameters `m,n,batchCount<0`
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublashpr()

cublasStatus_t cublasChpr(cublasHandle_t handle, cublasFillMode_t uplo,int n, const float *alpha,const cuComplex       *x, int incx,cuComplex       *AP)
cublasStatus_t cublasZhpr(cublasHandle_t handle, cublasFillMode_t uplo,int n, const double *alpha,const cuDoubleComplex *x, int incx,cuDoubleComplex *AP)

此函数支持64位整数接口。
此函数执行压缩厄米特秩-1更新

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix `A` lower or upper part is stored, the other Hermitian part is not referenced and is inferred from the stored elements.
n		input	number of rows and columns of matrix `A`.
alpha	host or device	input	scalar used for multiplication.
x	device	input	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.
A	device	in/out	array of dimensions `lda x n`, with `lda>=max(1,n)`. The imaginary parts of the diagonal elements are assumed and set to zero.
lda		input	leading dimension of two-dimensional array used to store matrix `A`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or if `incx` == 0 or if `uplo` != `CUBLAS_FILL_MODE_UPPER`, `CUBLAS_FILL_MODE_LOWER` or if `lda` < max(1, `n`) or `alpha` == NULL
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublasher2()

cublasStatus_t cublasCher2(cublasHandle_t handle, cublasFillMode_t uplo,int n, const cuComplex       *alpha,const cuComplex       *x, int incx,const cuComplex       *y, int incy,cuComplex       *A, int lda)
cublasStatus_t cublasZher2(cublasHandle_t handle, cublasFillMode_t uplo,int n, const cuDoubleComplex *alpha,const cuDoubleComplex *x, int incx,const cuDoubleComplex *y, int incy,cuDoubleComplex *A, int lda)

此函数支持64位整数接口。
此函数执行厄米特秩2更新

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix `A` lower or upper part is stored, the other Hermitian part is not referenced and is inferred from the stored elements.
n		input	number of rows and columns of matrix `A`.
alpha	host or device	input	scalar used for multiplication.
x	device	input	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.
y	device	input	vector with `n` elements.
incy		input	stride between consecutive elements of `y`.
A	device	in/out	array of dimension `lda x n` with `lda>=max(1,n)`. The imaginary parts of the diagonal elements are assumed and set to zero.
lda		input	leading dimension of two-dimensional array used to store matrix `A`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or if `incx` == 0 or `incy` == 0 or if `uplo` != `CUBLAS_FILL_MODE_UPPER`, `CUBLAS_FILL_MODE_LOWER` or if `lda` < max(1, `n`) or `alpha` == NULL
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublashpmv()

cublasStatus_t cublasChpmv(cublasHandle_t handle, cublasFillMode_t uplo,int n, const cuComplex       *alpha,const cuComplex       *AP,const cuComplex       *x, int incx,const cuComplex       *beta,cuComplex       *y, int incy)
cublasStatus_t cublasZhpmv(cublasHandle_t handle, cublasFillMode_t uplo,int n, const cuDoubleComplex *alpha,const cuDoubleComplex *AP,const cuDoubleComplex *x, int incx,const cuDoubleComplex *beta,cuDoubleComplex *y, int incy)

此功能支持64位整数接口。此功能执行Hermitian包装的矩阵矢量乘法

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix `A` lower or upper part is stored, the other Hermitian part is not referenced and is inferred from the stored elements.
n		input	number of rows and columns of matrix `A`.
alpha	host or device	input	scalar used for multiplication.
AP	device	input	array with `A` stored in packed format. The imaginary parts of the diagonal elements are assumed to be zero.
x	device	input	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.
beta	host or device	input	scalar used for multiplication, if `beta==0` then `y` does not have to be a valid input.
y	device	in/out	vector with `n` elements.
incy		input	stride between consecutive elements of `y`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or if `incx` == 0 or `incy` == 0 or if `uplo` != `CUBLAS_FILL_MODE_UPPER`, `CUBLAS_FILL_MODE_LOWER` or `alpha` == NULL or `beta` == NULL
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublashbmv()

cublasStatus_t cublasChbmv(cublasHandle_t handle, cublasFillMode_t uplo,int n, int k, const cuComplex       *alpha,const cuComplex       *A, int lda,const cuComplex       *x, int incx,const cuComplex       *beta,cuComplex       *y, int incy)
cublasStatus_t cublasZhbmv(cublasHandle_t handle, cublasFillMode_t uplo,int n, int k, const cuDoubleComplex *alpha,const cuDoubleComplex *A, int lda,const cuDoubleComplex *x, int incx,const cuDoubleComplex *beta,cuDoubleComplex *y, int incy)

此函数支持64位整数接口。
This function performs the Hermitian banded matrix-vector multiplication

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix `A` lower or upper part is stored, the other Hermitian part is not referenced and is inferred from the stored elements.
n		input	number of rows and columns of matrix `A`.
k		input	number of sub- and super-diagonals of matrix `A`.
alpha	host or device	input	scalar used for multiplication.
A	device	input	array of dimensions `lda x n`, with `lda>=k+1`. The imaginary parts of the diagonal elements are assumed to be zero.
lda		input	leading dimension of two-dimensional array used to store matrix `A`.
x	device	input	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.
beta	host or device	input	scalar used for multiplication, if `beta==0` then does not have to be a valid input.
y	device	in/out	vector with `n` elements.
incy		input	stride between consecutive elements of `y`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or `k` < 0 or if `incx` = 0 or `incy` = 0 or if `uplo` != `CUBLAS_FILL_MODE_LOWER`, `CUBLAS_FILL_MODE_UPPER` or if `lda` < (`k` + 1) or `alpha` == NULL or `beta` == NULL
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublashemv()

cublasStatus_t cublasChemv(cublasHandle_t handle, cublasFillMode_t uplo,int n, const cuComplex       *alpha,const cuComplex       *A, int lda,const cuComplex       *x, int incx,const cuComplex       *beta,cuComplex       *y, int incy)
cublasStatus_t cublasZhemv(cublasHandle_t handle, cublasFillMode_t uplo,int n, const cuDoubleComplex *alpha,const cuDoubleComplex *A, int lda,const cuDoubleComplex *x, int incx,const cuDoubleComplex *beta,cuDoubleComplex *y, int incy)

此函数支持64位整数接口。
此函数执行厄米特矩阵-向量乘法

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix `A` lower or upper part is stored, the other Hermitian part is not referenced and is inferred from the stored elements.
n		input	number of rows and columns of matrix `A`.
alpha	host or device	input	scalar used for multiplication.
A	device	input	array of dimension `lda x n`, with `lda>=max(1,n)`. The imaginary parts of the diagonal elements are assumed to be zero.
lda		input	leading dimension of two-dimensional array used to store matrix `A`.
x	device	input	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.
beta	host or device	input	scalar used for multiplication, if `beta==0` then `y` does not have to be a valid input.
y	device	in/out	vector with `n` elements.
incy		input	stride between consecutive elements of `y`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or if `incx` = 0 or `incy` = 0 or if `uplo` != `CUBLAS_FILL_MODE_LOWER`, `CUBLAS_FILL_MODE_UPPER` or `lda` < `n`
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublastrsv()

cublasStatus_t cublasStrsv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, const float           *A, int lda,float           *x, int incx)
cublasStatus_t cublasDtrsv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, const double          *A, int lda,double          *x, int incx)
cublasStatus_t cublasCtrsv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, const cuComplex       *A, int lda,cuComplex       *x, int incx)
cublasStatus_t cublasZtrsv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, const cuDoubleComplex *A, int lda,cuDoubleComplex *x, int incx)

此函数支持64位整数接口。
此函数求解具有单个右侧边的三角线性系统

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix `A` lower or upper part is stored, the other part is not referenced and is inferred from the stored elements.
trans		input	operation op(`A`) that is non- or (conj.) transpose.
diag		input	indicates if the elements on the main diagonal of matrix `A` are unity and should not be accessed.
n		input	number of rows and columns of matrix `A`.
A	device	input	array of dimension `lda x n`, with `lda>=max(1,n)`.
lda		input	leading dimension of two-dimensional array used to store matrix `A`.
x	device	in/out	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or if `incx` = 0 or if `trans` != `CUBLAS_OP_N`, `CUBLAS_OP_C`, `CUBLAS_OP_T` or if `uplo` != `CUBLAS_FILL_MODE_LOWER`, `CUBLAS_FILL_MODE_UPPER` or if `diag` != `CUBLAS_DIAG_UNIT`, `CUBLAS_DIAG_NON_UNIT` or `lda` < max(1, `n`)
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublastrmv()

cublasStatus_t cublasStrmv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, const float           *A, int lda,float           *x, int incx)
cublasStatus_t cublasDtrmv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, const double          *A, int lda,double          *x, int incx)
cublasStatus_t cublasCtrmv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, const cuComplex       *A, int lda,cuComplex       *x, int incx)
cublasStatus_t cublasZtrmv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, const cuDoubleComplex *A, int lda,cuDoubleComplex *x, int incx)

此函数支持64位整数接口。
此函数执行三角矩阵-向量乘法

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix `A` lower or upper part is stored, the other part is not referenced and is inferred from the stored elements.
trans		input	operation op(`A`) (that is, non- or conj.) transpose.
diag		input	indicates if the elements on the main diagonal of matrix `A` are unity and should not be accessed.
n		input	number of rows and columns of matrix `A`.
A	device	input	array of dimensions `lda x n` , with `lda>=max(1,n)`.
lda		input	leading dimension of two-dimensional array used to store matrix `A`.
x	device	in/out	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or if `incx` = 0 or if `trans` != `CUBLAS_OP_N`, `CUBLAS_OP_C`, `CUBLAS_OP_T` or if `uplo` != `CUBLAS_FILL_MODE_LOWER`, `CUBLAS_FILL_MODE_UPPER` or if `diag` != `CUBLAS_DIAG_UNIT`, `CUBLAS_DIAG_NON_UNIT` or `lda` < max(1, `n`)
`CUBLAS_STATUS_ALLOC_FAILED`	the allocation of internal scratch memory failed
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublastpsv()

cublasStatus_t cublasStpsv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, const float           *AP,float           *x, int incx)
cublasStatus_t cublasDtpsv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, const double          *AP,double          *x, int incx)
cublasStatus_t cublasCtpsv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, const cuComplex       *AP,cuComplex       *x, int incx)
cublasStatus_t cublasZtpsv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, const cuDoubleComplex *AP,cuDoubleComplex *x, int incx)

此函数支持64位整数接口。
此函数求解具有单个右侧边的压缩三角线性系统

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix `A` lower or upper part is stored, the other part is not referenced and is inferred from the stored elements.
trans		input	operation op(`A`) that is non- or (conj.) transpose.
diag		input	indicates if the elements on the main diagonal of matrix are unity and should not be accessed.
n		input	number of rows and columns of matrix `A`.
AP	device	input	array with `A` stored in packed format.
x	device	in/out	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or if `incx` = 0 or if `trans` != `CUBLAS_OP_N`, `CUBLAS_OP_C`, `CUBLAS_OP_T` or if `uplo` != `CUBLAS_FILL_MODE_LOWER`, `CUBLAS_FILL_MODE_UPPER` or `diag` != `CUBLAS_DIAG_UNIT`, `CUBLAS_DIAG_NON_UNIT`
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublastpmv()

cublasStatus_t cublasStpmv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, const float           *AP,float           *x, int incx)
cublasStatus_t cublasDtpmv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, const double          *AP,double          *x, int incx)
cublasStatus_t cublasCtpmv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, const cuComplex       *AP,cuComplex       *x, int incx)
cublasStatus_t cublasZtpmv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, const cuDoubleComplex *AP,cuDoubleComplex *x, int incx)

此函数支持64位整数接口。
此函数求解具有单个右侧边的压缩三角线性系统

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix `A` lower or upper part is stored, the other part is not referenced and is inferred from the stored elements.
trans		input	operation op(`A`) that is non- or (conj.) transpose.
diag		input	indicates if the elements on the main diagonal of matrix `A` are unity and should not be accessed.
n		input	number of rows and columns of matrix `A`.
AP	device	input	array with � stored in packed format.
x	device	in/out	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n < 0` or if `incx == 0` or if `uplo != CUBLAS_FILL_MODE_UPPER, CUBLAS_FILL_MODE_LOWER` or if `trans != CUBLAS_OP_N, CUBLAS_OP_T, CUBLAS_OP_C` or `diag != CUBLAS_DIAG_UNIT, CUBLAS_DIAG_NON_UNIT`
`CUBLAS_STATUS_ALLOC_FAILED`	the allocation of internal scratch memory failed
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublastbsv()

cublasStatus_t cublasStbsv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, int k, const float           *A, int lda,float           *x, int incx)
cublasStatus_t cublasDtbsv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, int k, const double          *A, int lda,double          *x, int incx)
cublasStatus_t cublasCtbsv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, int k, const cuComplex       *A, int lda,cuComplex       *x, int incx)
cublasStatus_t cublasZtbsv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, int k, const cuDoubleComplex *A, int lda,cuDoubleComplex *x, int incx)

此函数支持64位整数接口。
此函数求解具有单个右侧边的三角带状线性系统

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix `A` lower or upper part is stored, the other part is not referenced and is inferred from the stored elements.
trans		input	operation op(`A`) that is non- or (conj.) transpose.
diag		input	indicates if the elements on the main diagonal of matrix `A` are unity and should not be accessed.
n		input	number of rows and columns of matrix `A`.
k		input	number of sub- and super-diagonals of matrix `A`.
A	device	input	array of dimension `lda x n`, with `lda >= k+1`.
lda		input	leading dimension of two-dimensional array used to store matrix `A`.
x	device	in/out	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or `k` < 0 or if `incx` = 0 or if `trans` != `CUBLAS_OP_N`, `CUBLAS_OP_C`, `CUBLAS_OP_T` or if `uplo` != `CUBLAS_FILL_MODE_LOWER`, `CUBLAS_FILL_MODE_UPPER` or if `diag` != `CUBLAS_DIAG_UNIT`, `CUBLAS_DIAG_NON_UNIT` or `lda` < (1 + `k`)
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublastbmv()

cublasStatus_t cublasStbmv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, int k, const float           *A, int lda,float           *x, int incx)
cublasStatus_t cublasDtbmv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, int k, const double          *A, int lda,double          *x, int incx)
cublasStatus_t cublasCtbmv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, int k, const cuComplex       *A, int lda,cuComplex       *x, int incx)
cublasStatus_t cublasZtbmv(cublasHandle_t handle, cublasFillMode_t uplo,cublasOperation_t trans, cublasDiagType_t diag,int n, int k, const cuDoubleComplex *A, int lda,cuDoubleComplex *x, int incx)

此函数支持64位整数接口。
此函数用于执行三角带矩阵向量乘法

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix `A` lower or upper part is stored, the other part is not referenced and is inferred from the stored elements.
trans		input	operation op(`A`) that is non- or (conj.) transpose.
diag		input	indicates if the elements on the main diagonal of matrix `A` are unity and should not be accessed.
n		input	number of rows and columns of matrix `A`.
k		input	number of sub- and super-diagonals of matrix .
A	device	input	array of dimension `lda x n`, with `lda>=k+1`.
lda		input	leading dimension of two-dimensional array used to store matrix `A`.
x	device	in/out	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or `k` < 0 or if `incx` = 0 or if `trans` != `CUBLAS_OP_N`, `CUBLAS_OP_C`, `CUBLAS_OP_T` or if `uplo` != `CUBLAS_FILL_MODE_LOWER`, `CUBLAS_FILL_MODE_UPPER` or if `diag` != `CUBLAS_DIAG_UNIT`, `CUBLAS_DIAG_NON_UNIT` or `lda` < (1 + `k`)
`CUBLAS_STATUS_ALLOC_FAILED`	the allocation of internal scratch memory failed
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublassyr2()

cublasStatus_t cublasSsyr2(cublasHandle_t handle, cublasFillMode_t uplo, int n,const float           *alpha, const float           *x, int incx,const float           *y, int incy, float           *A, int lda
cublasStatus_t cublasDsyr2(cublasHandle_t handle, cublasFillMode_t uplo, int n,const double          *alpha, const double          *x, int incx,const double          *y, int incy, double          *A, int lda
cublasStatus_t cublasCsyr2(cublasHandle_t handle, cublasFillMode_t uplo, int n,const cuComplex       *alpha, const cuComplex       *x, int incx,const cuComplex       *y, int incy, cuComplex       *A, int lda
cublasStatus_t cublasZsyr2(cublasHandle_t handle, cublasFillMode_t uplo, int n,const cuDoubleComplex *alpha, const cuDoubleComplex *x, int incx,const cuDoubleComplex *y, int incy, cuDoubleComplex *A, int lda

此函数支持64位整数接口。
此函数执行对称秩2更新

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix `A` lower or upper part is stored, the other symmetric part is not referenced and is inferred from the stored elements.
n		input	number of rows and columns of matrix `A`.
alpha	host or device	input	scalar used for multiplication.
x	device	input	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.
y	device	input	vector with `n` elements.
incy		input	stride between consecutive elements of `y`.
A	device	in/out	array of dimensions `lda x n`, with `lda>=max(1,n)`.
lda		input	leading dimension of two-dimensional array used to store matrix `A`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or if `incx` = 0 or `incy` = 0 or if `uplo` != `CUBLAS_FILL_MODE_LOWER`, `CUBLAS_FILL_MODE_UPPER` or if `alpha` == NULL or `lda` < max(1, `n`)
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublassyr()

cublasStatus_t cublasSsyr(cublasHandle_t handle, cublasFillMode_t uplo,int n, const float           *alpha,const float           *x, int incx, float           *A, int lda)
cublasStatus_t cublasDsyr(cublasHandle_t handle, cublasFillMode_t uplo,int n, const double          *alpha,const double          *x, int incx, double          *A, int lda)
cublasStatus_t cublasCsyr(cublasHandle_t handle, cublasFillMode_t uplo,int n, const cuComplex       *alpha,const cuComplex       *x, int incx, cuComplex       *A, int lda)
cublasStatus_t cublasZsyr(cublasHandle_t handle, cublasFillMode_t uplo,int n, const cuDoubleComplex *alpha,const cuDoubleComplex *x, int incx, cuDoubleComplex *A, int lda)

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix `A` lower or upper part is stored, the other symmetric part is not referenced and is inferred from the stored elements.
n		input	number of rows and columns of matrix `A`.
alpha	host or device	input	scalar used for multiplication.
x	device	input	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.
A	device	in/out	array of dimensions `lda x n`, with `lda>=max(1,n)`.
lda		input	leading dimension of two-dimensional array used to store matrix `A`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or if `incx` = 0 or if `uplo` != `CUBLAS_FILL_MODE_LOWER`, `CUBLAS_FILL_MODE_UPPER` or if `lda` < max(1, `n`) or `alpha` == NULL
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublassymv()

cublasStatus_t cublasSsymv(cublasHandle_t handle, cublasFillMode_t uplo,int n, const float           *alpha,const float           *A, int lda,const float           *x, int incx, const float           *beta,float           *y, int incy)
cublasStatus_t cublasDsymv(cublasHandle_t handle, cublasFillMode_t uplo,int n, const double          *alpha,const double          *A, int lda,const double          *x, int incx, const double          *beta,double          *y, int incy)
cublasStatus_t cublasCsymv(cublasHandle_t handle, cublasFillMode_t uplo,int n, const cuComplex       *alpha, /* host or device pointer */const cuComplex       *A, int lda,const cuComplex       *x, int incx, const cuComplex       *beta,cuComplex       *y, int incy)
cublasStatus_t cublasZsymv(cublasHandle_t handle, cublasFillMode_t uplo,int n, const cuDoubleComplex *alpha,const cuDoubleComplex *A, int lda,const cuDoubleComplex *x, int incx, const cuDoubleComplex *beta,cuDoubleComplex *y, int incy)

此函数支持64位整数接口。
此函数执行对称矩阵向量乘法。

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix lower or upper part is stored, the other symmetric part is not referenced and is inferred from the stored elements.
n		input	number of rows and columns of matrix `A`.
alpha	host or device	input	scalar used for multiplication.
A	device	input	array of dimension `lda x n` with `lda>=max(1,n)`.
lda		input	leading dimension of two-dimensional array used to store matrix `A`.
x	device	input	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.
beta	host or device	input	scalar used for multiplication, if `beta==0` then `y` does not have to be a valid input.
y	device	in/out	vector with `n` elements.
incy		input	stride between consecutive elements of `y`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or if `incx` = 0 or `incy` = 0 or if `uplo` != `CUBLAS_FILL_MODE_LOWER`, `CUBLAS_FILL_MODE_UPPER` or `lda` < `n`
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublassbmv()

cublasStatus_t cublasSsbmv(cublasHandle_t handle, cublasFillMode_t uplo,int n, int k, const float  *alpha,const float  *A, int lda,const float  *x, int incx,const float  *beta, float *y, int incy)
cublasStatus_t cublasDsbmv(cublasHandle_t handle, cublasFillMode_t uplo,int n, int k, const double *alpha,const double *A, int lda,const double *x, int incx,const double *beta, double *y, int incy)

This function supports the 64-bit Integer Interface.

This function performs the symmetric banded matrix-vector multiplication

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
uplo		input	indicates if matrix `A` lower or upper part is stored, the other symmetric part is not referenced and is inferred from the stored elements.
n		input	number of rows and columns of matrix `A`.
k		input	number of sub- and super-diagonals of matrix `A`.
alpha	host or device	input	scalar used for multiplication.
A	device	input	array of dimension `lda x n` with `\lda >= k+1`.
lda		input	leading dimension of two-dimensional array used to store matrix `A`.
x	device	input	vector with `n` elements.
incx		input	stride between consecutive elements of `x`.
beta	host or device	input	scalar used for multiplication, if `beta==0` then `y` does not have to be a valid input.
y	device	in/out	vector with `n` elements.
incy		input	stride between consecutive elements of `y`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `n` < 0 or `k` < 0 or if `incx` = 0 or `incy` = 0 or if `uplo` != `CUBLAS_FILL_MODE_LOWER`, `CUBLAS_FILL_MODE_UPPER` or if `alpha` == NULL or `beta` == NULL or `lda` < (1 + `k`)
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublasger()

cublasStatus_t  cublasSger(cublasHandle_t handle, int m, int n,const float           *alpha,const float           *x, int incx,const float           *y, int incy,float           *A, int lda)
cublasStatus_t  cublasDger(cublasHandle_t handle, int m, int n,const double          *alpha,const double          *x, int incx,const double          *y, int incy,double          *A, int lda)
cublasStatus_t cublasCgeru(cublasHandle_t handle, int m, int n,const cuComplex       *alpha,const cuComplex       *x, int incx,const cuComplex       *y, int incy,cuComplex       *A, int lda)
cublasStatus_t cublasCgerc(cublasHandle_t handle, int m, int n,const cuComplex       *alpha,const cuComplex       *x, int incx,const cuComplex       *y, int incy,cuComplex       *A, int lda)
cublasStatus_t cublasZgeru(cublasHandle_t handle, int m, int n,const cuDoubleComplex *alpha,const cuDoubleComplex *x, int incx,const cuDoubleComplex *y, int incy,cuDoubleComplex *A, int lda)
cublasStatus_t cublasZgerc(cublasHandle_t handle, int m, int n,const cuDoubleComplex *alpha,const cuDoubleComplex *x, int incx,const cuDoubleComplex *y, int incy,cuDoubleComplex *A, int lda)

This function supports the 64-bit Integer Interface.

This function performs the rank-1 update

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
m		input	number of rows of matrix `A`.
n		input	number of columns of matrix `A`.
alpha	host or device	input	scalar used for multiplication.
x	device	input	vector with `m` elements.
incx		input	stride between consecutive elements of `x`.
y	device	input	vector with `n` elements.
incy		input	stride between consecutive elements of `y`.
A	device	in/out	array of dimension `lda x n` with `lda >= max(1,m)`.
lda		input	leading dimension of two-dimensional array used to store matrix `A`.

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	If `m` < 0 or `n` < 0 if `incx` = 0 or `incy` = 0 or if `alpha` == NULL or `lda` < max(1, `m`)
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

cublasgemv()

cublasStatus_t cublasSgemv(cublasHandle_t handle, cublasOperation_t trans,int m, int n,const float           *alpha,const float           *A, int lda,const float           *x, int incx,const float           *beta,float           *y, int incy)
cublasStatus_t cublasDgemv(cublasHandle_t handle, cublasOperation_t trans,int m, int n,const double          *alpha,const double          *A, int lda,const double          *x, int incx,const double          *beta,double          *y, int incy)
cublasStatus_t cublasCgemv(cublasHandle_t handle, cublasOperation_t trans,int m, int n,const cuComplex       *alpha,const cuComplex       *A, int lda,const cuComplex       *x, int incx,const cuComplex       *beta,cuComplex       *y, int incy)
cublasStatus_t cublasZgemv(cublasHandle_t handle, cublasOperation_t trans,int m, int n,const cuDoubleComplex *alpha,const cuDoubleComplex *A, int lda,const cuDoubleComplex *x, int incx,const cuDoubleComplex *beta,cuDoubleComplex *y, int incy)

Param.	Memory	In/out	Meaning
handle		input	handle to the cuBLAS library context.
trans		input	operation op(`A`) that is non- or (conj.) transpose.
m		input	number of rows of matrix `A`.
n		input	number of columns of matrix `A`.
alpha	host or device	input	scalar used for multiplication.
A	device	input	array of dimension `lda x n` with `lda >= max(1,m)`. Before entry, the leading `m` by `n` part of the array `A` must contain the matrix of coefficients. Unchanged on exit.
lda		input	leading dimension of two-dimensional array used to store matrix `A`. `lda` must be at least `max(1,m)`.
x	device	input	vector at least `(1+(n-1)abs(incx))` elements if `transa==CUBLAS_OP_N` and at least `(1+(m-1)abs(incx))` elements otherwise.
incx		input	stride between consecutive elements of `x`.
beta	host or device	input	scalar used for multiplication, if `beta==0` then `y` does not have to be a valid input.
y	device	in/out	vector at least `(1+(m-1)abs(incy))` elements if `transa==CUBLAS_OP_N` and at least `(1+(n-1)abs(incy))` elements otherwise.
incy		input	stride between consecutive elements of `y`

The possible error values returned by this function and their meanings are listed below.

Error Value	Meaning
`CUBLAS_STATUS_SUCCESS`	the operation completed successfully
`CUBLAS_STATUS_NOT_INITIALIZED`	the library was not initialized
`CUBLAS_STATUS_INVALID_VALUE`	the parameters `m,n<0` or `incx,incy=0`
`CUBLAS_STATUS_EXECUTION_FAILED`	the function failed to launch on the GPU

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cuBLAS使用(3)

cublasgbmv()

cublasspr()

cublasspr2()

cublasspmv()

cublasspr()

cublasgemvStridedBatched()

cublasgemvBatched()

cublashpr()

cublasher2()

cublashpmv()

cublashbmv()

cublashemv()

cublastrsv()

cublastrmv()

cublastpsv()

cublastpmv()

cublastbsv()

cublastbmv()

cublassyr2()

cublassyr()

cublassymv()

cublassbmv()

cublasger()

cublasgemv()

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cuBLAS使用(3)

cublasgbmv()

cublasspr()

​​​​​​cublasspr2()

cublasspmv()

cublasspr()

cublasgemvStridedBatched()

cublasgemvBatched()

cublashpr()

cublasher2()

cublashpmv()

cublashbmv()

cublashemv()

cublastrsv()

cublastrmv()

cublastpsv()

cublastpmv()

cublastbsv()

cublastbmv()

cublassyr2()

cublassyr()

cublassymv()

cublassbmv()

cublasger()

cublasgemv()

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热门资讯

cublasspr2()