GCSim: A GPU-Based Trace-Driven Simulator for Multi-level Cache

Abstract

We describe the design of parallel trace-driven cache simulation for the purposes of evaluating different cache structures. As the research goes deeper, traditional simulation methods, which can only execute simulation operations in sequence, are no longer practical due to their long simulation cycles. An obvious way to achieve fast parallel simulation is to simulate the independent sets of a cache concurrently on different compute resources. We considered the use of generic GPU to accelerate cache simulation which exploits set-partitioning as the main source of parallelism. But we show this technique is not efficient in the case that just simulating one cache configuration, since a high correlation of the activity between different sets. Trace-sort and multi-configuration simulation in one single pass techniques are developed, taking advantage of the full programmability offered by the Compute Unified Device Architecture (CUDA) on the GPU. Our experimental results demonstrate that the cache simulator based on GPU-CPU platform gains 2.44x performance improvement compared to traditional sequential algorithm.