Memory access patterns of parallel scientific programs

Abstract

A parallel simulator, PSIMUL, has been used to collect information on the memory access patterns and synchronization overheads of several scientific applications. The parallel simulation method we use is very efficient and it allows us to simulate execution of an entire application program, amounting to hundreds of millions of instructions. We present our measurements on the memory access characteristics of these applications; particularly our observations on shared and private data, their frequency of access and locality. We have found that, even though the shared data comprise the largest portion of the data in the application program, on the average a small fraction of the memory references are to shared data. The low averages do not preclude bursts of traffic to shared memory nor does it rule out positive benefits from caching shared data. We also discuss issues of synchronization overheads and their effect on performance.