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A scalable high performance cholesky factorization for multicore with gpu accelerators,” university of tennessee, lapack working note 223 (2009).
| Content Provider | CiteSeerX |
|---|---|
| Author | Ltaief, H. Tomov, S. Nath, R. Du, P. Dongarra, J. |
| Abstract | Abstract. We present a Cholesky factorization for multicore with GPU accelerators systems. The challenges in developing scalable high performance algorithms for these emerging systems stem from their heterogeneity, massive parallelism, and the huge gap between the GPUs ’ compute power vs the CPU-GPU communication speed. We show an approach that is largely based on software infrastructures that have already been developed for homogeneous multicores and hybrid GPU-based computing. This results in a scalable hybrid Cholesky factorization of unprecedented performance. In particular, using NVIDIA’s Tesla S1070 (4 C1060 GPUs, each with 30 cores @1.44 GHz) connected to two dual-core AMD Opteron |
| File Format | |
| Publisher Date | 2009-01-01 |
| Access Restriction | Open |
| Content Type | Text |