Dynamic data prefetching in home-based software DSMs
Journal of Computer Science and Technology
Optimizing Home-Based Software DSM Protocols
Cluster Computing
JIAJIA: A Software DSM System Based on a New Cache Coherence Protocol
HPCN Europe '99 Proceedings of the 7th International Conference on High-Performance Computing and Networking
Reducing System Overheads in Home-based Software DSMs
IPPS '99/SPDP '99 Proceedings of the 13th International Symposium on Parallel Processing and the 10th Symposium on Parallel and Distributed Processing
A Comparison of Two Strategies of Dynamic Data Prefetching in Software DSM
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Write Detection in Home-Based Software DSMs
Euro-Par '99 Proceedings of the 5th International Euro-Par Conference on Parallel Processing
Dynamic Task Migration in Home-based Software DSM Systems
HPDC '99 Proceedings of the 8th IEEE International Symposium on High Performance Distributed Computing
Evaluation of the JIAJIA Software DSM System on High Performance Computer Architectures
HICSS '99 Proceedings of the Thirty-second Annual Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Adaptive Granularity: Transparent Integration of Fine- and Coarse-Grain Communications
PACT '96 Proceedings of the 1996 Conference on Parallel Architectures and Compilation Techniques
On Design of Agent Home Scheme for Prefetching Strategy in DSM Systems
AINA '05 Proceedings of the 19th International Conference on Advanced Information Networking and Applications - Volume 1
On the Design and Implementation of an Effective Prefetch Strategy for DSM Systems
The Journal of Supercomputing
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Distributed Shared Memory (DSM) environment is built by using specific softwares, to combine a number of computer hardware resources into one computing environment. Such environment not only provides an easy way to execute parallel applications, but also combines resources to speedup execution of these applications. DSM systems need to maintain data consistency in memory, what usually leads to communication overhead. Therefore, there exist a number of strategies that can be used to overcome this overhead and improve overall performance. Prefetching strategies have been proven to show great performance in DSM systems, since they can reduce data access communication latencies from remote nodes. However, these strategies also transfer unnecessary prefetching pages to remote nodes. In this research paper, we focus on the analysis of data access pattern during execution of parallel applications. We propose an Adaptive Data Classification scheme to improve prefetching strategy, with the goal to improve overall performance. Adaptive Data Classification scheme classifies data according to the access behavior of pages, so that home node uses past history access patterns of remote nodes to decide whether it needs to transfer related pages to remote nodes. From experimental results, our method can improve the performance of prefetching strategies in DSM systems.