Andrew Reisner

Legacy codes are in ubiquitous use in scientific simulations; they are well-tested and there is significant time investment in their use. However, one challenge is the adoption of new, sometimes incompatible computing paradigms, such as GPU hardware. In this paper, we explore using automated code translation to enable execution of legacy multigrid solver code on GPUs without significant time investment and while avoiding intrusive changes to the codebase. We developed a thin, reusable translation layer that parses Fortran 2003 at compile time, interfacing with the existing library Loopy ( Klöckner, 2014 ) to transpile to C ++ /GPU code, which is then managed by a custom MPI runtime system that we created. With this low-effort approach, we are able to achieve a payoff of an approximately 2–3× speedup over a full CPU socket, and 6× in multi-node settings.

The ASC Advanced Technology Development and Mitigation (ATDM) sub-program was established in2014to develop new simulation tools operating on exascale-class computers to serve NNSA (see Appendix B). Over the course of ATDM, LANL management have set a strategy for exascale-class application codes that follows two supportive and mutually risk-mitigating paths: evolution for established production integrated design codes (IDCs) – with a strong pedigree within the user community – based upon existing programming paradigms(MPI+X); and a new start ATDM project, Ristra, a high-risk/high-reward push for a next-generation multi-physics, multi-scale simulation toolkit based on emerging advanced programming systems(with an initial focus on data-flow task-based models exemplified by Legion). The role of Ristra as the high-risk/high-reward path for LANL’s codes was fully consistent with the goals of ATDM as described in Appendix B, in particular its emphasis on evolving ASC capabilities through novel computing programming models and computing technologies.