PRESTO: a system for object-oriented parallel programming
Software—Practice & Experience
Munin: distributed shared memory based on type-specific memory coherence
PPOPP '90 Proceedings of the second ACM SIGPLAN symposium on Principles & practice of parallel programming
Dynamic node reconfiguration in a parallel-distributed environment
PPOPP '91 Proceedings of the third ACM SIGPLAN symposium on Principles and practice of parallel programming
Lazy release consistency for software distributed shared memory
ISCA '92 Proceedings of the 19th annual international symposium on Computer architecture
Per-Node Multithreading and Remote Latency
IEEE Transactions on Computers
Thread migration and its applications in distributed shared memory systems
Journal of Systems and Software
ICDCS '99 Proceedings of the 19th IEEE International Conference on Distributed Computing Systems
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Abstract: Parallel applications executing on large system size of parallel systems achieve better speedup than on small system size. However, because of the design and implementation of the Distributed Shared Memory (DSM) system, there are some instances that large system size has no further performance improvement over small system size. It is important to determine what system size will result in the maximum speedup while all kinds of applications are running on DSM systems. In this paper, we describe the design and implementation of the performance prediction mechanism in our DSM system, Proteus [13], which supports node reconfiguration to adjust system size at runtime. We adopt a simple computation model and combine it with runtime information to predict the performance under different system sizes. With this work, it is possible to provide timely prediction result for the underlying system to adjust system size and thus maximize speedup.