StructSlim: a lightweight profiler to guide structure splitting

Abstract

Memory access latency continues to be a dominant bottleneck in a large class of applications on modern architectures. To optimize memory performance, it is important to utilize the locality in the memory hierarchy. Structure splitting can significantly improve memory locality. However, pinpointing inefficient code and providing insightful guidance for structure splitting is challenging. Existing tools typically leverage heavyweight memory instrumentations, which hinders the applicability of these tools for real long-running programs. To address this issue, we develop StructSlim, a profiler to pinpoint top candidates that benefit from structure splitting. StructSlim makes three unique contributions. First, it adopts lightweight address sampling to collect and analyze memory traces. Second, StructSlim employs a set of novel methods to determine memory access patterns to guide structure splitting. We also formally prove that our method has high accuracy even with sparse memory access samples. Third, StructSlim scales on multithreaded machines. StructSlim works on fully optimized, unmodified binary executables independently from their compiler and language, incurring around 7% runtime overhead. To evaluate StructSlim, we study seven sequential and parallel benchmarks. With the guidance of StructSlim, we are able to significantly improve all these benchmarks; the speedup is up to 1.37x.