Dynamic scheduling on a PC cluster
Proceedings of the 1999 ACM symposium on Applied computing
Non-Strict Cache Coherence: Exploiting Data-Race Tolerance in Emerging Applications
ICPP '00 Proceedings of the Proceedings of the 2000 International Conference on Parallel Processing
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Software distributed shared memory (DSM) platforms on networks of workstations tolerate large network latencies by employing one of several weak memory consistency models. Fully asynchronous parallel iterative algorithms offer an additional degree of freedom to tolerate network latency: they behave correctly when supplied outdated shared data. However, these algorithms can flood the network with messages in the presence of large delays. We propose a method of controlling asynchronous iterative methods wherein the reader of a shared datum imposes an upper bound on its age via use of a blocking Global\_Read primitive. This reduces the overall number of iterations executed by the reader, thus controlling the amount of shared updates generated. Experiments for a fully asynchronous linear equation solver running on a network of 10 IBM RS/6000 workstations show that the proposed Global\_Read primitive provides significant performance improvement.