SC16 Salt Lake City, UT

13. Accelerating PETSc-Based CFD Codes with Multi-GPU Computing

Authors: Pi-Yueh Chuang (George Washington University)Lorena A. Barba (George Washington University)

Abstract: We wrote a wrapper code to bridge PETSc and AmgX libraries to use AmgX's multi-GPU linear solvers in existing PETSc-based CFD codes. With the wrapper, those codes are able to exploit all available CPU and GPU resources without heavy coding efforts. The wrapper features a simple usage: the two functions for setting and solving a linear system in the wrapper can directly replace the same functions in PETSc. Data conversion, transfer, scatters and gathers, and MPI communications are all taken care of. Benchmarks with real CFD applications show that, with multi-GPU computing, we can save 1) run times and hardware cost (e.g. a 6-CPU-core workstation with 1 NVIDIA K40c can compete with a 16-node CPU cluster); and 2) cloud HPC cost (e.g. a benchmark on Amazon EC2 shows a 16x cost saving between CPU and GPU clusters).

Poster: pdf
Two-page extended abstract: pdf

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