Performs a symmetric rank-2k update.
event syr2k(queue &exec_queue, uplo upper_lower, transpose trans, std::int64_t n, std::int64_t k, T alpha, const T* a, std::int64_t lda, const T* b, std::int64_t ldb, T beta, T* c, std::int64_t ldc, const vector_class<event> &dependencies = {});
The USM version of syr2k supports the following precisions and devices:
T | Devices Supported |
---|---|
float | Host, CPU, and GPU |
double | Host, CPU, and GPU |
std::complex<float> | Host, CPU, and GPU |
std::complex<double> | Host, CPU, and GPU |
The syr2k routines perform a rank-2k update of an n x n symmetric matrix C by general matrices A and B. If trans = transpose::nontrans, the operation is defined as:
C <- alpha*(A*BT + B*AT) + beta*C
where A is n x k and B is k x n.
If trans = transpose::trans, the operation is defined as:
C <- alpha*(AT*B + BT*A) + beta*C
where A is k x n and B is n x k.
In both cases:
alpha and beta are scalars,
C is a symmetric matrix and A, B are general matrices,
The inner dimension of both matrix multiplications is k.
The queue where the routine should be executed.
Specifies whether A's data is stored in its upper or lower triangle. See Data Types for more details.
Specifies the operation to apply, as described above. Conjugation is never performed, even if trans = transpose::conjtrans.
Number of rows and columns in C. The value of n must be at least zero.
Inner dimension of matrix multiplications.The value of k must be at least zero.
Scaling factor for the rank-2k update.
Pointer to input matrix A. If trans = transpose::nontrans, A is an n-by-k matrix so the array a must have size at least lda*k (respectively, lda*n) if column (respectively, row) major layout is used to store matrices. Otherwise, A is an k-by-n matrix so the array a must have size at least lda*n (respectively, lda*k) if column (respectively, row) major layout is used to store matrices. See Matrix and Vector Storage for more details.
Leading dimension of A. If matrices are stored using column major layout, lda must be at least n if trans=transpose::nontrans, and at least k otherwise. If matrices are stored using row major layout, lda must be at least k if trans=transpose::nontrans, and at least n otherwise. Must be positive.
Pointer to input matrix B. If trans = transpose::nontrans, B is an k-by-n matrix so the array b must have size at least ldb*n (respectively, ldb*k) if column (respectively, row) major layout is used to store matrices. Otherwise, B is an n-by-k matrix so the array b must have size at least ldb*k (respectively, ldb*n) if column (respectively, row) major layout is used to store matrices. See Matrix and Vector Storage for more details.
Leading dimension of B. If matrices are stored using column major layout, ldb must be at least k if trans = transpose::nontrans, and at least n otherwise. If matrices are stored using row major layout, ldb must be at least n if trans = transpose::nontrans, and at least k otherwise. Must be positive.
Scaling factor for matrix C.
Pointer to input/output matrix C. Must have size at least ldc*n. See Matrix and Vector Storage for more details
Leading dimension of C. Must be positive and at least n.
List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies.
Pointer to the output matrix, overwritten by the updated C matrix.
Output event to wait on to ensure computation is complete.