2016/09/12 by Hofmann Johannes, Hofmann, Johannes, Fey Dietmar +1
Computer Science · #Advanced Data Storage Technologies #Cloud Computing and Resource Management #FOS: Computer and information sciences #Parallel Computing and Optimization Techniques #Performance (cs.PF)
paper · pdf · doi:10.48550/arxiv.1609.03347
openalex publication_date 2016/09/12 · openalex created_date 2017/08/31 · openalex updated_date 2026/07/28
We investigate an approach that uses low-level analysis and the execution-cache-memory (ECM) performance model in combination with tuning of hardware parameters to lower energy requirements of memory-bound applications. The ECM model is extended appropriately to deal with software optimizations such as non-temporal stores. Using incremental steps and the ECM model, we analytically quantify the impact of various single-core optimizations and pinpoint microarchitectural improvements that are relevant to energy consumption. Using a 2D Jacobi solver as example that can serve as a blueprint for other memory-bound applications, we evaluate our approach on the four most recent Intel Xeon E5 processors (Sandy Bridge-EP, Ivy Bridge-EP, Haswell-EP, and Broadwell-EP). We find that chip energy consumption can be reduced in the range of 2.0-2.4× on the examined processors.