BOAST: A metaprogramming framework to produce portable and efficient computing kernels for HPC applications. (January 2018)

• Record Type: Journal Article
• Authors: Videau, Brice; Pouget, Kevin; Genovese, Luigi; Deutsch, Thierry; Komatitsch, Dimitri; Desprez, Frédéric; Méhaut, Jean-François
• Other Names: Dongarra Jack guest-editor.; Tourancheau Bernard guest-editor.
• Is Part Of: International journal of high performance computing applications. Volume 32:Number 1(2018)
• Page Start: 28
• Page End: 44
• Publication Date: 2018-01
• Subjects: Code generation -- portability -- genericity -- autotuning -- nonregression -- testing -- productivity and software design -- high-performance computing; High performance computing -- Periodicals; Supercomputers -- Periodicals; 004.1105
• DOI: 10.1177/1094342017718068
• Languages: English
• ISSNs: 1094-3420

Abstract

The portability of real high-performance computing (HPC) applications on new platforms is an open and very delicate problem. Especially, the performance portability of the underlying computing kernels is problematic as they need to be tuned for each and every platform the application encounters. This article presents BOAST, a metaprogramming framework dedicated to computing kernels. BOAST allows the description of a kernel and its possible optimizations using a domain-specific language. BOAST runtime will then compare the different versions'performance as well as verify their exactness. BOAST is applied to three use cases: a Laplace kernel in OpenCL and two HPC applications BigDFT (electronic density computation) and SPECFEM3D (seismic and wave propagation).