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Issue No. 02 - Feb. (2018 vol. 29)
ISSN: 1045-9219
pp: 269-282
Robert Lyerly , Bradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA
Alastair Murray , Bradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA
Antonio Barbalace , Bradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA
Binoy Ravindran , Bradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA
ABSTRACT
Heterogeneous-ISA computing platforms have become ubiquitous, and will be used for diverse workloads which render static mappings of computation to processors inadequate. Dynamic mappings which adjust an application's usage in consideration of platform workload can reduce application latency and increase throughput for heterogeneous platforms. We introduce AIRA, a compiler and runtime for flexible execution of applications in CPU-GPU platforms. Using AIRA, we demonstrate up to a 3.78x speedup in benchmarks from Rodinia and Parboil, run with various workloads on a server-class platform. Additionally, AIRA is able to extract up to an 87 percent increase in platform throughput over a static mapping.
INDEX TERMS
Computer architecture, Kernel, Runtime, Graphics processing units, Throughput, Atmospheric modeling
CITATION

R. Lyerly, A. Murray, A. Barbalace and B. Ravindran, "AIRA: A Framework for Flexible Compute Kernel Execution in Heterogeneous Platforms," in IEEE Transactions on Parallel & Distributed Systems, vol. 29, no. 2, pp. 269-282, 2018.
doi:10.1109/TPDS.2017.2761748
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