Automated data-member layout of heap objects to improve memory-hierarchy performance

Abstract

We present and evaluate a simple, yet efficient optimization technique that improves memory-hierarchy performance for pointer-centric applications by up to 24% and reduces cache misses by up to 35%. This is achieved by selecting an improved ordering for the data members of pointer-based data structures. Our optimization is applicable to all type-safe programming languages that completely abstract from physical storage layout; examples of such languages are Java and Oberon. Our technique does not involve programmers in the optimization process, but runs fully automatically, guided by dynamic profiling information that captures which paths through the program are taken with what frequency. The algorithm first strives to cluster data members that are accessed closely after one another onto the same cache line, increasing spatial locality. Then, the data members that have been mapped to a particular cache line are ordered to minimize load latency in case of a cache miss.