Logo Questions Linux Laravel Mysql Ubuntu Git Menu
 

Transpose matrix multiplication in cuBLAS howto

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!

like image 667
user1522407 Avatar asked Dec 12 '22 18:12

user1522407


1 Answers

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 if 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.

like image 186
kangshiyin Avatar answered Dec 14 '22 23:12

kangshiyin