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I was testing clsparse on Nvidia gtx 690 because I want to rewrite my cuda code into opencl for it support much more platforms. While I was testing clsparseScsrmm(), the sparse-dense matrix multiply routine, I found that no matter what major the dense matrix is set(cldenseMatrix mat; mat.major = rowMajor; or mat.major = columnMajor; ), clsparseScsrmm() always reads and writes data in row major. For more specific situation, when I set major to rowMajor I get correct result, otherwise I get wrong result. Then I tested the columnMajor and find it reads and writes data in rowMajor.
Thank you guys very much for helping me with this.
Usher
The text was updated successfully, but these errors were encountered:
UsherWang
changed the title
Probable bug in cldenseMatrix with clsparseScsrmm()
Probable bug in clsparseScsrmm() with cldenseMatrix
Apr 28, 2017
Same problem.
The reason is that the csrmm() function in clsparse-csrmm.hpp simply discards memory layout infomation. And it seems that authors won't fix the problem. Disappointed!
Hi there,
I was testing clsparse on Nvidia gtx 690 because I want to rewrite my cuda code into opencl for it support much more platforms. While I was testing clsparseScsrmm(), the sparse-dense matrix multiply routine, I found that no matter what major the dense matrix is set(cldenseMatrix mat; mat.major = rowMajor; or mat.major = columnMajor; ), clsparseScsrmm() always reads and writes data in row major. For more specific situation, when I set major to rowMajor I get correct result, otherwise I get wrong result. Then I tested the columnMajor and find it reads and writes data in rowMajor.
Thank you guys very much for helping me with this.
Usher
The text was updated successfully, but these errors were encountered: