Methods for compressible fluid simulation on GPUs using high-order finite differences

Tutkimustuotos: Lehtiartikkelivertaisarvioitu

Tutkijat

Organisaatiot

  • University of Helsinki
  • Max Planck Institute for Solar System Research
  • University of Potsdam
  • Nokia Siemens Networks
  • Aalto University

Kuvaus

We focus on implementing and optimizing a sixth-order finite-difference solver for simulating compressible fluids on a GPU using third-order Runge-Kutta integration. Since graphics processing units perform well in data-parallel tasks, this makes them an attractive platform for fluid simulation. However, high-order stencil computation is memory-intensive with respect to both main memory and the caches of the GPU. We present two approaches for simulating compressible fluids using 55-point and 19-point stencils. We seek to reduce the requirements for memory bandwidth and cache size in our methods by using cache blocking and decomposing a latency-bound kernel into several bandwidth-bound kernels. Our fastest implementation is bandwidth-bound and integrates 343 million grid points per second on a Tesla K40t GPU, achieving a 3.6× speedup over a comparable hydrodynamics solver benchmarked on two Intel Xeon E5-2690v3 processors. Our alternative GPU implementation is latency-bound and achieves the rate of 168 million updates per second.

Yksityiskohdat

AlkuperäiskieliEnglanti
Sivut11-22
JulkaisuComputer Physics Communications
Vuosikerta217
TilaJulkaistu - elokuuta 2017
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

ID: 12973950