Bulletin of the American Physical Society
APS April Meeting 2024
Wednesday–Saturday, April 3–6, 2024; Sacramento & Virtual
Session P06: Mini-Symposium: Connecting Nuclear Physics and Astrophysics III
3:45 PM–5:09 PM,
Friday, April 5, 2024
SAFE Credit Union Convention Center
Room: Ballroom A8, Floor 2
Sponsoring
Units:
DNP DAP
Chair: Andrew Steiner, University of Tennessee
Abstract: P06.00006 : Using Code Generation to Enhance Performance and Portability of Supernova Simulations*
4:45 PM–4:57 PM
Presenter:
Youngjun Lee
(Argonne National Laboratory)
Authors:
Youngjun Lee
(Argonne National Laboratory)
Johann Rudi
(Virginia Tech)
Aidan H Chadha
(Virginia Tech)
Mohamed Wahib
(Riken)
Klaus Weide
(University of Chicago)
Jared O'Neal
(Argonne National Laboratory)
Anshu Dubey
(Argonne National Laboratory)
Code generation provides a mechanism to mitigate this challenge. For Flash-X, a multiphysics software system for the simulation of various astrophysical phenomena, we have developed a methodology where suitable variants of solvers or time-steppers can be expressed in the form of a high-level pseudo-code-like recipe. CG-kit, a new code generation toolkit, parses the recipe that generates compilable code for the corresponding solver/time-stepper. We have applied this approach to Spark, the hydrodynamics solver in Flash-X, where optimal control flow varies for different platforms, even though the basic algorithm and computations remain identical. We maintain three different recipes instead of complete code for these variants, which are succinct. CG-Kit is used to generate the most suitable code for the target platform by selecting the appropriate recipe. An added advantage is that the generated code has a simpler control flow because the need for alternative branches is obviated. In this presentation, we describe our approach and its application to Spark.
*The Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration;The Scientific Discovery through Advanced Computing (SciDAC) program via the Office of Nuclear Physics and Office of Advanced Scientific Computing Research in the Office of Science at the U.S.\ Department of Energy under contracts DE-AC02-06CH11357 and % ANL DE-SC0023472. % VT
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