Past Event: Babuška Forum

A GPU-Accelerated AMR Solver for Gravitational Wave Propagation

Milinda Fernando, Postdoctoral fellow, Oden Institute, UT Austin

Abstract

Simulations to calculate a single gravitational waveform (GW) can take several weeks. Yet, thousands of such simulations are needed for the detection and interpretation of gravitational waves. Future detectors will require even more accurate waveforms than those currently used. We present here the first large-scale, adaptive mesh, multi-GPU numerical relativity (NR) code together with performance analysis and benchmarking. While comparisons are difficult to make, the GPU extension of the Dendro-GR NR code achieves a 6x speedup over existing state-of-the-art codes. We achieve 800 GFlops/s on a single NVIDIA A100 GPU with an overall 2.5x speedup over a two-socket, 128-core AMD EPYC 7763 CPU node with an equivalent CPU implementation. We present detailed performance analyses, parallel scalability results, and accuracy assessments for GWs computed for mass ratios q=1,2,4. We also present strong scalability up to 16 A100s and weak scaling up to 229,376 x86 cores on the Texas Advanced Computing Center's Frontera system.

Biography

Milinda Fernando is a postdoctoral fellow at the Oden Institute. His research is focused on developing algorithms and computational methods that enable the effective use of modern supercomputers to tackle problems in science and engineering.  It is driven by applications in computational general relativity,  computational fluid dynamics, and plasma physics. His previous research work resulted in the development of state-of-the-art distributed algorithms for adaptive mesh refinement, scalable mesh partitioning algorithms, and the numerical relativity framework Dendro-GR. He received his Ph.D. from the School of Computing at the Un