Abstract
This paper examines energy management in a heterogeneous processor consisting of an integrated CPU-GPU for high-performance computing (HPC) applications. Energy management for HPC applications is challenged by their uncompromising performance requirements and complicated by the need for coordinating energy management across distinct core types-a new and less understood problem. We examine the intra-node CPU-GPU frequency sensitivity of HPC applications on tightly coupled CPU-GPU architectures as the first step in understanding power and performance optimization for a heterogeneous multi-node HPC system. The insights from this analysis form the basis of a coordinated energy management scheme, called DynaCo, for integrated CPU-GPU architectures. We implement DynaCo on a modern heterogeneous processor and compare its performance to a state-of-the-art power- and performance-management algorithm. DynaCo improves measured average energy-delay squared (ED2) product by up to 30% with less than 2% average performance loss across several exascale and other HPC workloads. © 2014 - IOS Press and the authors. All rights reserved.
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Paul, I., Ravi, V., Manne, S., Arora, M., & Yalamanchili, S. (2014). Coordinated energy management in heterogeneous processors. Scientific Programming, 22(2), 93–108. https://doi.org/10.1155/2014/210762
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