问题
The problem is simple: I have two matrices, A and B, that are M by N, where M >> N. I want to first take the transpose of A, and then multiply that by B (A^T * B) to put that into C, which is N by N. I have everything set up for A and B, but how do I call cublasSgemm properly without it returning the wrong answer?
I understand that cuBlas has a cublasOperation_t enum for transposing things beforehand, but somehow I'm not quite using it correctly. My matrices A and B are in row-major order, i.e. [ row1 ][ row2 ][ row3 ]..... in device memory. That means for A to be interpreted as A-transposed, BLAS needs to know my A is in column-major order. My current code looks like below:
float *A, *B, *C;
// initialize A, B, C as device arrays, fill them with values
// initialize m = num_row_A, n = num_row_B, and k = num_col_A;
// set lda = m, ldb = k, ldc = m;
// alpha = 1, beta = 0;
// set up cuBlas handle ...
cublasSgemm(handle, CUBLAS_OP_T, CUBLAS_OP_N, m, n, k, &alpha, A, lda, B, ldb, &beta, C, ldc);
My questions:
Am I setting up m, k, n correctly?
What about lda, ldb, ldc?
Thanks!
回答1:
Since cuBLAS always assume that the matrices are stored in column-major. You could either transpose your matrices first into colum-major by using cublas_geam(), or
You could treat your matrix A stored in row-major, as a new matrix AT stored in column-major. The matrix AT is actually the transpose of A. For B do the same thing. Then you could calculate matrix C stored in column-major by C=AT * BT^T
float* AT = A;
float* BT = B;
The leading dimension is a param related to the storage, which doesn't change no matter you use the transpose flag CUBLAS_OP_T or not.
lda = num_col_A = num_row_AT = N;
ldb = num_col_B = num_row_BT = N;
ldc = num_row_C = N;
m and n in the cuBLAS GEMM routine are the #rows and #cols of the result matrix C,
m = num_row_C = num_row_AT = num_col_A = N;
n = num_col_C = num_row_BT = num_col_B = N;
k is the common dimension of A^T and B,
k = num_col_AT = num_row_B = M;
Then you could invoke the GEMM routine by
cublasSgemm(handle, CUBLAS_OP_N, CUBLAS_OP_T, m, n, k, &alpha, AT, lda, BT, ldb, &beta, C, ldc);
If you want the matrix C to be stored in row-major, you could calculate the CT stored in column-major with the formula CT = BT * AT^T by
cublasSgemm(handle, CUBLAS_OP_N, CUBLAS_OP_T, n, m, k, &alpha, BT, ldb, AT, lda, &beta, CT, ldc);
Please note you don't have to swap m and n since C is a square matrix in this case.
来源：https://stackoverflow.com/questions/14595750/transpose-matrix-multiplication-in-cublas-howto