Affiliations: Advanced Micro Devices, Inc., USA. E-mails: {indrani.paul, vignesh.ravi, srilatha.manne}@amd.com, [email protected] | Georgia Institute of Technology, Atlanta, GA, USA. E-mail: [email protected] | University of California, San Diego, CA, USA
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.
Keywords: Energy management, high-performance computing
