We assess the optimizations' impact on memory and runtime performance for a suite of cutting-edge computer architectures such has the NVIDIA V100 GPU, the IBM Power9, and the Fujitsu A64FX architectures. Our optimizations enable a 31.25% reduction in memory usage and up to 40% increase in the number of particles.
Dec 18, 2021 · Our optimizations enable a 31.25% reduction in memory usage and up to 40% increase in the number of particles.
Jan 31, 2022 · Our optimizations enable a 31.25% reduction in memory usage and up to 40% increase in the number of particles. This paper extends our work on ...
In this study, we present a suite of VPIC memory optimizations (i.e., particle weight, half-precision, and fixed-point optimizations) that enable a significant ...
Analysis of Vector Particle-In-Cell (VPIC) memory usage optimizations on cutting-edge computer architectures. https://doi.org/10.1016/j.jocs.2022.101566.
Current memory systems limit VPIC simulations greatly as the maximum number of particles that can be simulated directly depends on the available memory. In this ...
Excited to share our new paper on the analysis of Vector Particle-In-Cell (VPIC) memory usage optimizations on cutting-edge computer architectures.
Analysis of Vector Particle-In-Cell (VPIC) memory usage optimizations on cutting-edge computer architectures. Article. Jan 2022. Nigel Tan · Robert Bird ...
Aug 13, 2024 · Analysis of Vector Particle-In-Cell (VPIC) memory usage optimizations on cutting-edge computer architectures. J. Comput. Sci. 60: 101566 ...
Analysis of Vector Particle-In-Cell (VPIC) memory usage optimizations on cutting-edge computer architectures. N Tan, RF Bird, G Chen, SV Luedtke, BJ Albright ...