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ASF GitHub Bot commented on MAHOUT-1974: ---------------------------------------- Github user nsakharnykh commented on the issue: https://github.com/apache/mahout/pull/310 @andrewpalumbo regarding column-major: yes, this is the default mode for CUBLAS, sorry I think I didn't mention it in my original email. There are a couple options we can exercise here. 1. We can use transposed versions of `gemm` routines if the input matrices are row-major. I think the output matrix will be always column-major so we'll have to transpose it by using `geam` if we want to keep it in a different format. 2. We can also keep the dense matrices in column-major format on the GPU and move between `csc` and `csr` formats for sparse matrices by using CUSPARSE conversion routines like `csr2csc`. There are also existing API functions in CUSPARSE to convert sparse to dense `csr2dense` and the other way around `dense2csr`. I think we should try to use the available conversion APIs from CUSPARSE as much as possible to avoid writing this on our own. > CUDA support > ------------ > > Key: MAHOUT-1974 > URL: https://issues.apache.org/jira/browse/MAHOUT-1974 > Project: Mahout > Issue Type: New Feature > Reporter: Nikolay Sakharnykh > Labels: features > > Implement native CUDA bindings using JCuda -- This message was sent by Atlassian JIRA (v6.3.15#6346)