SC17 Denver, CO

Keynote - Application Development Framework for Manycore Architectures on Post-Peta/Exascale Systems

Workshop: 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems
Authors: Kengo Nakajima (University of Tokyo)

Abstract: "ppOpen-HPC" is an open source infrastructure for development and execution of optimized and reliable simulation code on post-peta-scale (pp) parallel computers based on manycore architectures. Source code developed on a PC with a single processor is linked and the parallel code generated is optimized for post-petascale systems with manycore architectures, such as the Oakforest-PACS system. "ppOpen-HPC" is part of a five-year project spawned by the "Development of System Software Technologies for Post-PetaScale High Performance Computing" funded by JST-CREST. The framework covers various types of procedures for scientific computations, such as parallel I/O of data-sets, matrix-assembly, linear-solvers with practical and scalable preconditioners, visualization, adaptive mesh refinement, and dynamic load-balancing, in various types of computational models, such as FEM, FDM, FVM, BEM and DEM. Automatic tuning technology enables automatic generation of optimized libraries and applications under various types of environments. We release the most updated version of ppOpen-HPC as open source software every year in November at . In 2016, the team of ppOpen-HPC joined ESSEX-II (Equipping Sparse Solvers for Exascale) project, which is funded by JST-CREST and the German DFG priority program 1648 "Software for Exascale Computing" (SPPEXA) under Japan-Germany collaboration. In ESSEX-II, we develop pK-Open-HPC (extended version of ppOpen-HPC, framework for exa-feasible applications), preconditioned iterative solvers for quantum sciences, and a framework for automatic tuning with performance model. In the presentation, various types of achievements of ppOpen-HPC, ESSEX-II, and pK-OpenHPC project, such as applications using HACApK library for H-matrix computation, and parallel preconditioned iterative solvers will be shown.

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