UC Berkeley

Overlapping communication with computation is an important optimization on current cluster architectures; its importance is likely to increase as the doubling of processing power far outpaces any improvements in communication latency. PGAS languages offer unique opportunities for communication overlap, because their one-sided communication model enables low overhead data transfer. Recent results have shown the value of hiding latency by manually applying language-level nonblocking data transfer routines, but this process can be both tedious and error-prone. In this paper, we present a runtime framework that automatically schedules the data transfers to achieve overlap. The optimization framework is entirely transparent to the user, and aggressively reorders and aggregates both remote puts and gets. We preserve correctness via runtime conflict checks and temporary buffers, using several techniques to lower the overhead. Experimental results on application benchmarks suggest that our framework can be very effective at hiding communication latency on clusters, improving performance over the blocking code by an average of 16% for some of the NAS Parallel Benchmarks, 48% for GUPS, and over 25% for a multi-block fluid dynamics solver. While the system is not yet as effective as aggressive manual optimization, it increases programmers’ productivity by freeing them from the details of communication management. Copyright 2007 ACM.