Abstract
This article provides a comprehensive study of the impact of performance optimizations on the energy efficiency of a real-world CFD application called MPDATA, as well as an insightful analysis of performance-energy interaction of these optimizations with the underlying hardware that represents the first generation of Intel Xeon Scalable processors. Considering the MPDATA iterative application as a use case, we explore the fundamentals of energy and performance analysis for a memory-bound application when exposed to a set of optimization steps that increase the application performance, by improving the operational intensity of code and utilizing resources more efficiently. It is shown that for memory-bound applications, optimizing toward high performance could be a powerful strategy for improving the energy efficiency as well. In fact, for the considered performance optimizations, the energy gain is correlated with the performance gain but with varying degrees. As a result, these optimizations allow improving both performance and energy consumption radically, up to about 10.9 and 8.8 times, respectively. The impact of the Intel AVX-512 SIMD extension on the energy consumption and performance is demonstrated. Also, we discover limitations on the usability of CPU frequency scaling as a tool for balancing energy savings with admissible performance losses.
Highlights
THE energy consumption of current and emerging supercomputers is still increasing despite improvements in the energy efficiency area
The main contributions of this work are: 1) For a real-world CFD application called multidimensional positive definite advection transport algorithm (MPDATA), we provide a comprehensive study of the impact of performance optimizations on the energy efficiency of application, as well as an insightful analysis of performance-energy interaction of these optimizations with the underlying hardware that represents the first generation of Intel Xeon Scalable processors
The analysis of results for all considered sizes of MPDATA domains show these improvements are in the range of 10.3910.94 and 8.27-8.76 for performance and energy consumption, respectively
Summary
THE energy consumption of current and emerging supercomputers is still increasing despite improvements in the energy efficiency area. The remarkable example is a family of Intel Xeon Scalable processors [4] that open promising opportunities to reduce the energy consumption of HPC applications, and to explore new tradeoffs between energy and performance. Another direction in energy-aware HPC is related to rethinking the software, including both execution environments and applications themselves. An example of research on modifying the execution environment is work [5], where an energy-aware task management mechanism is designed and evaluated for an iterative CFD (computational fluid dynamic) application – the multidimensional positive definite advection transport algorithm (MPDATA) [6] running. The detailed description of the MPDATA numerical scheme is presented in works [7], [34]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Parallel and Distributed Systems
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
