Understanding Energy Aspects of Processing-near-Memory for HPC Workloads

Abstract

Interests in the concept of processing-near-memory (PNM) have been reignited with recent improvements of the 3D integration technology. In this work, we analyze the energy consumption characteristics of a system which comprises a conventional processor and a 3D memory stack with fully-programmable cores. We construct a high-level analytical energy model based on the underlying architecture and the technology with which each component is built. From the preliminary experiments with 11 HPC benchmarks from Mantevo benchmark suite, we observed that misses per kilo instructions (MPKI) of last-level cache (LLC) is one of the most important characteristics in determining the friendliness of the application to the PNM execution.