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.