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Title: HACC: extreme scaling and performance across diverse architectures, In: SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis

Abstract

Supercomputing is evolving towards hybrid and accelerator-based architectures with millions of cores. The HACC (Hardware/Hybrid Accelerated Cosmology Code) framework exploits this diverse landscape at the largest scales of problem size, obtaining high scalability and sustained performance. Developed to satisfy the science requirements of cosmological surveys, HACC melds particle and grid methods using a novel algorithmic structure that flexibly maps across architectures, including CPU/GPU, multi/many-core, and Blue Gene systems. We demonstrate the success of HACC on two very different machines, the CPU/GPU system Titan and the BG/Q systems Sequoia and Mira, attaining unprecedented levels of scalable performance. We demonstrate strong and weak scaling on Titan, obtaining up to 99.2% parallel efficiency, evolving 1.1 trillion particles. On Sequoia, we reach 13.94 PFlops (69.2% of peak) and 90% parallel efficiency on 1,572,864 cores, with 3.6 trillion particles, the largest cosmological benchmark yet performed. HACC design concepts are applicable to several other supercomputer applications.

Authors:
; ; ; ; ;
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1567353
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Journal Article
Journal Name:
International Conference for High Performance Computing, Networking, Storage and Analysis
Additional Journal Information:
Conference: International Conference on High Performance Computing, Networking, Storage and Analysis, Denver, Colorado, November 17-21, 2013
Country of Publication:
United States
Language:
English
Subject:
Computer Science; Engineering

Citation Formats

Habib, Salman, Morozov, Vitali, Frontiere, Nicholas, Finkel, Hal, Pope, Adrian, and Heitmann, Katrin. HACC: extreme scaling and performance across diverse architectures, In: SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis. United States: N. p., 2013. Web. doi:10.1145/2503210.2504566.
Habib, Salman, Morozov, Vitali, Frontiere, Nicholas, Finkel, Hal, Pope, Adrian, & Heitmann, Katrin. HACC: extreme scaling and performance across diverse architectures, In: SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis. United States. doi:10.1145/2503210.2504566.
Habib, Salman, Morozov, Vitali, Frontiere, Nicholas, Finkel, Hal, Pope, Adrian, and Heitmann, Katrin. Tue . "HACC: extreme scaling and performance across diverse architectures, In: SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis". United States. doi:10.1145/2503210.2504566.
@article{osti_1567353,
title = {HACC: extreme scaling and performance across diverse architectures, In: SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis},
author = {Habib, Salman and Morozov, Vitali and Frontiere, Nicholas and Finkel, Hal and Pope, Adrian and Heitmann, Katrin},
abstractNote = {Supercomputing is evolving towards hybrid and accelerator-based architectures with millions of cores. The HACC (Hardware/Hybrid Accelerated Cosmology Code) framework exploits this diverse landscape at the largest scales of problem size, obtaining high scalability and sustained performance. Developed to satisfy the science requirements of cosmological surveys, HACC melds particle and grid methods using a novel algorithmic structure that flexibly maps across architectures, including CPU/GPU, multi/many-core, and Blue Gene systems. We demonstrate the success of HACC on two very different machines, the CPU/GPU system Titan and the BG/Q systems Sequoia and Mira, attaining unprecedented levels of scalable performance. We demonstrate strong and weak scaling on Titan, obtaining up to 99.2% parallel efficiency, evolving 1.1 trillion particles. On Sequoia, we reach 13.94 PFlops (69.2% of peak) and 90% parallel efficiency on 1,572,864 cores, with 3.6 trillion particles, the largest cosmological benchmark yet performed. HACC design concepts are applicable to several other supercomputer applications.},
doi = {10.1145/2503210.2504566},
journal = {International Conference for High Performance Computing, Networking, Storage and Analysis},
number = ,
volume = ,
place = {United States},
year = {2013},
month = {1}
}