Aira: A framework for flexible compute kernel execution in heterogeneous platforms

R Lyerly, A Murray, A Barbalace… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
IEEE Transactions on Parallel and Distributed Systems, 2017ieeexplore.ieee.org
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 3.78× speedup in benchmarks …
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 3.78× 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.
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