TY - JOUR
T1 - A comparison of three programming models for adaptive applications on the Origin2000
AU - Shan, Hongzhang
AU - Singh, Jaswinder Pal
AU - Oliker, Leonid
AU - Biswas, Rupak
N1 - Funding Information:
The work of the first two authors was supported by the National Science Foundation under Grant ESS-9806751. The second author was also supported by a Presidential Early Career Award for Scientists and Engineers (PECASE) and a Sloan Research Fellowship. The work of the third author was supported by the Office of Computational and Technology Research, Division of Mathematical, Information, and Computational Sciences of the U.S. Department of Energy under Contract DE-AC03-76SF00098. This manuscript won the Best Student Paper Award at the 2000 Supercomputing Conference (SC2000), held November 4–10 in Dallas, Texas.
PY - 2002
Y1 - 2002
N2 - Adaptive applications have computational workloads and communication patterns that 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 that 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.
AB - Adaptive applications have computational workloads and communication patterns that 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 that 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.
KW - Dynamic mesh adaptation
KW - Message passing
KW - N-body problem
KW - Parellel programming
KW - Shared address space
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U2 - 10.1006/jpdc.2001.1777
DO - 10.1006/jpdc.2001.1777
M3 - Article
AN - SCOPUS:0036195435
SN - 0743-7315
VL - 62
SP - 241
EP - 266
JO - Journal of Parallel and Distributed Computing
JF - Journal of Parallel and Distributed Computing
IS - 2
ER -