A comparison of three programming models for adaptive applications on the Origin2000

Hongzhang Shan, Jaswinder Pal Singh, Leonid Oliker, Rupak Biswas

Research output: Contribution to journalArticlepeer-review

21 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)241-266
Number of pages26
JournalJournal of Parallel and Distributed Computing
Issue number2
StatePublished - 2002

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence


  • Dynamic mesh adaptation
  • Message passing
  • N-body problem
  • Parellel programming
  • Shared address space


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