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New basic linear algebra methods for simulation on GPUs
| Content Provider | Semantic Scholar |
|---|---|
| Author | Shi, Jian Zhang, Yiwei Langland, Blake Tang, Jijun Dougal, Roger A. |
| Copyright Year | 2011 |
| Abstract | We have used Graphics Processing Units (GPUs) to accelerate the solution of the types of equations typically encountered in dynamic system simulators. Compared to commercial matrix solvers that run on a CPU, we realized speedups ranging from 5 (for system size ≈ 700) to 460 (for system size ≈ 5800). While calculation time for the commercial matrix solver increased with matrix size ≈ O(N)2.3, our new GPU-based Preconditioned Generalized Minimal Residual (PGM-RES) technique yielded scaling as ≈ O(N)1.2. A significant component of this performance was achieved by development of new Basic Linear Algebra routines for the NVIDIA Tesla GPU that directly address characteristics typical of matrices that describe the time domain response of naturally-coupled dynamic systems. |
| Starting Page | 258 |
| Ending Page | 265 |
| Page Count | 8 |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://vtb.engr.sc.edu/vtbwebsite/downloads/publications/New%20Basic%20Linear%20Algebra%20Methods.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
