English

Paraiso : An Automated Tuning Framework for Explicit Solvers of Partial Differential Equations

Instrumentation and Methods for Astrophysics 2015-06-04 v2 Distributed, Parallel, and Cluster Computing Neural and Evolutionary Computing

Abstract

We propose Paraiso, a domain specific language embedded in functional programming language Haskell, for automated tuning of explicit solvers of partial differential equations (PDEs) on GPUs as well as multicore CPUs. In Paraiso, one can describe PDE solving algorithms succinctly using tensor equations notation. Hydrodynamic properties, interpolation methods and other building blocks are described in abstract, modular, re-usable and combinable forms, which lets us generate versatile solvers from little set of Paraiso source codes. We demonstrate Paraiso by implementing a compressive hydrodynamics solver. A single source code less than 500 lines can be used to generate solvers of arbitrary dimensions, for both multicore CPUs and GPUs. We demonstrate both manual annotation based tuning and evolutionary computing based automated tuning of the program.

Keywords

Cite

@article{arxiv.1204.4779,
  title  = {Paraiso : An Automated Tuning Framework for Explicit Solvers of Partial Differential Equations},
  author = {Takayuki Muranushi},
  journal= {arXiv preprint arXiv:1204.4779},
  year   = {2015}
}

Comments

52 pages, 14 figures, accepted for publications in Computational Science and Discovery