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| Title | Comparing Hybrid CPU-GPU and Native GPU-only Acceleration for Linear Algebra |
| Publication Type | Conference Paper |
| Year of Publication | 2015 |
| Authors | Gates, M., S. Tomov, and A. Haidar |
| Conference Name | 2015 SIAM Conference on Applied Linear Algebra |
| Date Published | 2015-10 |
| Publisher | SIAM |
| Conference Location | Atlanta, GA |
| Abstract | Accelerating dense linear algebra using GPUs admits two models: hybrid CPU-GPU and GPU-only. The hybrid model factors the panel on the CPU while updating the trailing matrix on the GPU, concentrating the GPU on high-performance matrix multiplies. The GPU-only model performs the entire computation on the GPU, avoiding costly data transfers to the CPU. We compare these two approaches for three QR-based algorithms: QR factorization, rank revealing QR, and reduction to Hessenberg. |
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