Title
Achieving Exascale Capabilities through Heterogeneous Computing
Abstract
AbstractThis article provides an overview of AMD's vision for exascale computing, and in particular, how heterogeneity will play a central role in realizing this vision. Exascale computing requires high levels of performance capabilities while staying within stringent power budgets. Using hardware optimized for specific functions is much more energy efficient than implementing those functions with general-purpose cores. However, there is a strong desire for supercomputer customers not to have to pay for custom components designed only for high-end high-performance computing systems. Therefore, high-volume GPU technology becomes a natural choice for energy-efficient data-parallel computing. To fully realize the GPU's capabilities, the authors envision exascale computing nodes that compose integrated CPUs and GPUs (that is, accelerated processing units), along with the hardware and software support to enable scientists to effectively run their scientific experiments on an exascale system. The authors discuss the hardware and software challenges in building a heterogeneous exascale system and describe ongoing research efforts at AMD to realize their exascale vision.
Year
DOI
Venue
2015
10.1109/MM.2015.71
Periodicals
Field
DocType
Volume
Exascale computing,Computer architecture,Unconventional computing,Supercomputer,Computer science,Efficient energy use,Parallel computing,Symmetric multiprocessor system,Real-time computing,Software,Memory management,Bandwidth (signal processing)
Journal
35
Issue
ISSN
Citations 
4
0272-1732
14
PageRank 
References 
Authors
0.61
11
10
Name
Order
Citations
PageRank
Michael J. Schulte1101587.86
Mike Ignatowski219211.60
Gabriel H. Loh32481134.10
Bradford Beckmann42390101.06
William C. Brantley5435144.62
Sudhanva Gurumurthi6123278.23
Nuwan Jayasena768545.83
Indrani Paul81279.88
Steven K. Reinhardt93885226.69
Gregory Rodgers10151.01