Keynote - Application Development Framework for Manycore
Architectures on Post-Peta/Exascale Systems
Author/Presenters
Event Type
Workshop
Algorithms
Exascale
Resiliency
SIGHPC Workshop
TimeMonday, November 13th9:05am -
9:45am
Location607
Description"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
http://ppopenhpc.cc.u-tokyo.ac.jp/ppopenhpc/ . 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.
