Warping Cache Simulation of Polyhedral Programs

TL;DR

This paper introduces warping cache simulation, a hybrid method combining analytical and explicit simulation techniques to efficiently evaluate cache performance of polyhedral programs with problem-size-independent runtime.

Contribution

It presents a novel hybrid approach that enables fast, accurate cache simulation for polyhedral programs, bridging the gap between traditional and analytical methods.

Findings

Achieves cache simulation runtimes often independent of memory access count

Combines analytical reasoning with explicit cache simulation for efficiency

Applicable to real-world cache models and large problem sizes

Abstract

Techniques to evaluate a program's cache performance fall into two camps: 1. Traditional trace-based cache simulators precisely account for sophisticated real-world cache models and support arbitrary workloads, but their runtime is proportional to the number of memory accesses performed by the program under analysis. 2. Relying on implicit workload characterizations such as the polyhedral model, analytical approaches often achieve problem-size-independent runtimes, but so far have been limited to idealized cache models. We introduce a hybrid approach, warping cache simulation, that aims to achieve applicability to real-world cache models and problem-size-independent runtimes. As prior analytical approaches, we focus on programs in the polyhedral model, which allows to reason about the sequence of memory accesses analytically. Combining this analytical reasoning with information about the cache behavior obtained from explicit cache simulation allows us to soundly fast-forward the simulation. By this process of warping, we accelerate the simulation so that its cost is often independent of the number of memory accesses.