SilkRoad: a multithreaded runtime system with software distributed shared memory for SMP clusters

Constructing multithreaded parallel systems with software distributed shared memory (DSM) is an attractive trend in cluster computing. Distributed Cilk (Cilk 5.1) is a multithreaded runtime system for SMP clusters with support for the divide-and-conquer programming paradigm. However, it lacks suppor...

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Bibliographic Details
Published in:2000 IEEE International Conference on Cluster Computing pp. 243 - 249
Main Authors: Peng, L., Wong, W.F., Feng, M.D., Yuen, C.K.
Format: Conference Proceeding
Language:English
Published: IEEE 2000
Subjects:
Concurrent computing
Control systems
Distributed computing
Multithreading
Programming profession
Software performance
Software systems
Software testing
System testing
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ISBN:9780769508962, 0769508960
Online Access:Get full text
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Summary:Constructing multithreaded parallel systems with software distributed shared memory (DSM) is an attractive trend in cluster computing. Distributed Cilk (Cilk 5.1) is a multithreaded runtime system for SMP clusters with support for the divide-and-conquer programming paradigm. However, it lacks support for user-level shared memory. We describe SilkRoad, an extension of Distributed Cilk which implements the lazy release consistency (LRC) memory model. In the SilkRoad runtime system, system control information is kept consistent by means of a backing store, just as it is in the original Distributed Cilk, while the user's cluster wide shared data is kept consistent by LRC. LRC enables SilkRoad programmers to define and use shared variables between the threads running on different nodes in a cluster This greatly enlarges the scope of supported programming paradigms in Cilk. Besides testing its performance, we also compared SilkRoad with TreadMarks, an LRC software DSM system for clusters with no support of multithreading. The results show that with the hybrid memory model of dag-consistency and LRC, multithreaded SilkRoad programs written in a divide-and-conquer fashion with good data locality can achieve comparable performance with the corresponding multiple-process TreadMarks programs.
ISBN:9780769508962
0769508960
DOI:10.1109/CLUSTR.2000.889067