Experiments on the Effectiveness of an Automatic Insertion of Memory Reuses into ML-like Programs

Abstract

We present extensive experimental results on our static analysis and source-level transformation [12, 11] that adds explicit memory-reuse commands into ML program text. Our analysis and transformation cost is negligible (1,582 to 29,000 lines per seconds) enough to be used in daily programming. The payoff is the reduction of memory peaks and the total garbage collection time. The transformed programs reuse 3.4% to 93.9% of total allocated memory cells, and the memory peak is reduced by 0.0% to 71.9%. When the memory peak reduction is large enough to overcome the costs of dynamic flags and the memory reuse in the generational garbage collection, it speeds up programs execution by up to 39.1%. Otherwise, our transformation can slowdown programs by up to 7.3%. The speedup is likely only when the portion of garbage collection time among the total execution time is more than about 30%. Copyright 2004 ACM.