Porting WarpX to GPU-accelerated platforms
A. Myers, A. Almgren, L. D. Amorim, J. Bell, L. Fedeli, L. Ge, K., Gott, D. P. Grote, M. Hogan, A. Huebl, R. Jambunathan, R. Lehe, C. Ng, M., Rowan, O. Shapoval, M. Th\'evenet, J.-L. Vay, H. Vincenti, E. Yang, N., Za\"im, W. Zhang, Y. Zhao, E. Zoni
TL;DR
This paper discusses the adaptation of WarpX, an electromagnetic particle-in-cell code, to GPU-accelerated platforms, highlighting strategies, challenges, lessons learned, and performance results on supercomputers.
Contribution
It presents a comprehensive strategy for porting WarpX to GPU architectures, enabling efficient use on supercomputers like Summit, Frontier, and Aurora.
Findings
WarpX achieves improved performance on GPU-accelerated nodes.
Identified key challenges and solutions in GPU porting of scientific codes.
Performance benchmarks demonstrate scalability and efficiency.
Abstract
WarpX is a general purpose electromagnetic particle-in-cell code that was originally designed to run on many-core CPU architectures. We describe the strategy followed to allow WarpX to use the GPU-accelerated nodes on OLCF's Summit supercomputer, a strategy we believe will extend to the upcoming machines Frontier and Aurora. We summarize the challenges encountered, lessons learned, and give current performance results on a series of relevant benchmark problems.
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