A comparison of three programming models for adaptive applications on the Origin2000
Journal Article
·
· Journal of Parallel and Distributed Computing
OSTI ID:838170
- LBNL Library
Adaptive applications have computational workloads and communication patterns which change unpredictably at runtime, requiring dynamic load balancing to achieve scalable performance on parallel machines. Efficient parallel implementations of such adaptive applications is therefore a challenging task. In this paper, we compare the performance of and the programming effort required for two major classes of adaptive applications under three leading parallel programming models on an SGI Origin2000 system, a machine which supports all three models efficiently. Results indicate that the three models deliver comparable performance; however, the implementations differ significantly beyond merely using explicit messages versus implicit loads/stores even though the basic parallel algorithms are similar. Compared with the message-passing (using MPI) and SHMEM programming models, the cache-coherent shared address space (CC-SAS) model provides substantial ease of programming at both the conceptual and program orchestration levels, often accompanied by performance gains. However, CC-SAS currently has portability limitations and may suffer from poor spatial locality of physically distributed shared data on large numbers of processors.
- Research Organization:
- Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, CA (US)
- Sponsoring Organization:
- USDOE. Office of Computational and Technology Research Division. Mathematical Information and Computational Sciences; National Science Foundation Grant ESS-9806751; Presidential Early Career Award for Scientists and Engineers, Sloan Research Fellowship (US)
- DOE Contract Number:
- AC03-76SF00098
- OSTI ID:
- 838170
- Report Number(s):
- LBNL--48811
- Journal Information:
- Journal of Parallel and Distributed Computing, Journal Name: Journal of Parallel and Distributed Computing Journal Issue: 2 Vol. 62
- Country of Publication:
- United States
- Language:
- English
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