Paper Info
Title
Analyzing the performance/power tradeoff of the rCUDA middleware for future exascale systems
Abstract
The computing power of supercomputers and data centers has noticeably grown during the last decades at the cost of an ever increasing energy demand. The need for energy (and power) of these facilities has finally limited the evolution of high performance computing, making that many researchers are concerned not only about performance but also about energy efficiency. However, despite the many concerns about energy consumption, the search for computing power continues. In this regard, the research on exascale systems, able to deliver 1018 floating point operations per second, has reached a widely consensus that these systems should operate within a maximum power budget of 20 megawatts. Many efficiency improvements are necessary for achieving this goal. One of these improvements is the usage of ARM low-power processors, as the Mont-Blanc project proposes. In this paper we analyze the combined use of ARM processors with the rCUDA remote GPU virtualization middleware as a way to improve efficiency even more. Results show that it is possible to speed up applications by almost 8x while reducing energy consumption up to 35% when rCUDA is used to access high-end GPUs. These improvements are achieved while maintaining a feasible average power consumption level for future exascale systems.
Year
DOI
Venue
2019
10.1016/j.jpdc.2019.04.021
Journal of Parallel and Distributed Computing
Keywords
Field
DocType
GPU virtualization,HPC,Energy,Exascale
Middleware,Virtualization,ARM architecture,Supercomputer,Efficient energy use,Computer science,Maximum power principle,Energy consumption,Distributed computing,Speedup
Journal
Volume
ISSN
Citations 
132
0743-7315
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Carlos Reaño113115.02
Javier Prades2307.15
Federico Silla357656.77