PEPERONI: Pre-Estimating the Performance of Near-Memory Integration
Oliver Lenke, Richard Petri, Thomas J. Wild, Andreas Herkersdorf · 2021
Near-memory integration strives to tackle the challenge of low data locality and power consumption originating from cross- chip data transfers, meanwhile referred to as locality wall. In order to keep costly engineering efforts bounded when transforming an existing non-near-memory architecture into a near-memory instance, reliable performance estimation during early design stages is needed. We propose PEPERONI, an agile performance estimation model to predict the runtime of representative benchmarks under near-memory acceleration on an MPSoC prototype. By relying solely on measurements of an existing baseline architecture, the method provides reliable estimations on the performance of near-memory processing units before their expensive implementation. The model is based on a quantitative description of memory boundedness and is independent of algorithmic knowledge, what facilitates its applicability to various applications.