New basic linear algebra methods for simulation on GPUs

Authors:
Jian Shi;Yiwei Zhang;Blake langland;Jijun Tang;Roger Dougal
Affiliations:
University of South Carolina, Columbia SC;University of South Carolina, Columbia SC;University of South Carolina, Columbia SC;University of South Carolina, Columbia SC;University of South Carolina, Columbia SC
Venue:
Proceedings of the 2011 Grand Challenges on Modeling and Simulation Conference
Year:
2011

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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.