LU, QR and Cholesky factorizations using GPU Options

[vvolkov]

I'd like to share an implementation of LAPACK's routines SGETRF, SPOTRF, and SGEQRF that is accelerated using GPU. This implementation is limited to factorization of square matrices that reside in the host memory (i.e. at the CPU side). The following figure shows the sustained performance on the following platform: Intel Core2 Quad 2.83 GHz (Q9550), PCIe 2.0 x16, Intel MKL 10.1, Windows XP 64-bit, NVIDIA driver 181.20, CUDA 2.1:

The implementation follows the description given in the following paper; however, some of the finer tunings described, such as recursive and variable blocking, are not included in this release:

Volkov, V., and Demmel, J. W. 2008. Benchmarking GPUs to tune dense linear algebra, SC08.

Regards,

Vasily

05/02/09 edit: updated dead URL to the paper.

This post has been edited by vvolkov: May 2 2009, 12:30 PM

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