Performance-Portable Many-Core Plasma Simulations: Porting PIConGPU to OpenPower and Beyond

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

Abstract

With the appearance of the heterogeneous platform Open-Power, many-core accelerator devices have been coupled with Power host processors for the first time. Towards utilizing their full potential, it is worth investigating performance portable algorithms that allow to choose the best-fitting hardware for each domain-specific compute task. Suiting even the high level of parallelism on modern GPGPUs, our presented approach relies heavily on abstract meta-programming techniques, which are essential to focus on fine-grained tuning rather than code porting. With this in mind, the CUDA-based open-source plasma simulation code PIConGPU is currently being abstracted to support the heterogeneous OpenPower platform using our fast porting interface cupla, which wraps the abstract parallel C++11 kernel acceleration library Alpaka.

We demonstrate how PIConGPU can benefit from the tunable kernel execution strategies of the Alpaka library, achieving portability and performance with single-source kernels on conventional CPUs, Power8 CPUs and NVIDIA GPUs.

Details

OriginalspracheEnglisch
TitelHigh Performance Computing
Redakteure/-innenM Taufer, B Mohr, JM Kunkel
Herausgeber (Verlag)Springer, Berlin [u. a.]
Seiten293-301
Seitenumfang9
ISBN (Print)978-3-319-46078-9
PublikationsstatusVeröffentlicht - 2016
Peer-Review-StatusJa

Publikationsreihe

ReiheLecture Notes in Computer Science, Volume 9945
ISSN0302-9743

Konferenz

TitelInternational Supercomputing Conference (ISC High Performance)
Dauer19 - 23 Juni 2016
StadtFrankfurt
LandDeutschland

Externe IDs

Scopus 84992665616

Schlagworte

Schlagwörter

  • OpenPower, Heterogeneous computing, HPC, C++11, CUDA, OpenMP, Particle-in-cell, Platform portability, Performance portability

Bibliotheksschlagworte