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Summary: Characterizing and Evaluating a Key-value Store
Application on Heterogeneous CPU-GPU Systems
Tayler H. Hetherington Timothy G. Rogers Lisa Hsu§ Mike O'Connor§ Tor M. Aamodt
Department of Electrical and Computer Engineering
University of British Columbia, Vancouver, BC, CANADA
{taylerh,tgrogers,aamodt}@ece.ubc.ca
§
Advanced Micro Devices, Inc. (AMD)
{Lisa.Hsu,Mike.OConnor}@amd.com
Abstract--The recent use of graphics processing units (GPUs)
in several top supercomputers demonstrate their ability to con-
sistently deliver positive results in high-performance computing
(HPC). GPU support for significant amounts of parallelism would
seem to make them strong candidates for non-HPC applications
as well. Server workloads are inherently parallel; however, at
first glance they may not seem suitable to run on GPUs due
to their irregular control flow and memory access patterns.
In this work, we evaluate the performance of a widely used
key-value store middleware application, Memcached, on recent
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