Data prefetching for software DSMs

In this paper we propose and evaluate the Adaptive++ technique, a novel runtime-only data prefetching strategy for software-based distributed shared-memory systems (software DSMs).Adaptive++ improves the performance of regular parallel applications running on software DSMs by using the past history of memory access faults to adapt between repeated-phase and repeated-stride prefetching modes.Adaptive++ does not issue prefetches during periods when the application is not exhibiting one of these two types of behavior and is thus behaving irregularly.Through detailed execution-driven simulations of several applications, we show that our prefetching technique is very successful at reducing the data access overheads of regular applications running on the TreadMarks software DSM.Adaptive++ also reduces the overhead of applications that are not strictly regular but that exhibit periods of regularity.In terms of overall performance, our results show that Adaptive++ can provide speedup improvements as significant as 34% on 16 processors.A direct comparison against two runtime-only prefetching techniques proposed thus far shows that Adaptive++ is consistently competitive in terms of performance, while being able to optimize a larger set of applications.Our main conclusion is that Adaptive++ should definitely be considered by software DSM designers as an effective way of tolerating the overhead of remote data accesses.Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commen: ial advantage and that copies bear this notice and the full citation on the fust page.To oopy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific pe-rmission and/or a fee.