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Dynamic thread assignment on heterogeneous multiprocessor architectures
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Source Conference On Computing Frontiers archive
Proceedings of the 3rd conference on Computing frontiers table of contents
Ischia, Italy
SESSION: Multithreaded, multicore, and SoC systems table of contents
Pages: 29 - 40  
Year of Publication: 2006
ISBN:1-59593-302-6
Authors
Michela Becchi  Washington University, St. Louis, MO
Patrick Crowley  Washington University, St. Louis, MO
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 31,   Downloads (12 Months): 152,   Citation Count: 5
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ABSTRACT

In a multi-programmed computing environment, threads of execution exhibit different runtime characteristics and hardware resource requirements. Not only do the behaviors of distinct threads differ, but each thread may also present diversity in its performance and resource usage over time. A heterogeneous chip multiprocessor (CMP) architecture consists of processor cores and caches of varying size and complexity. Prior work has shown that heterogeneous CMPs can meet the needs of a multi-programmed computing environment better than a homogeneous CMP system. In fact, the use of a combination of cores with different caches and instruction issue widths better accommodates threads with different computational requirements.A central issue in the design and use of heterogeneous systems is to determine an assignment of tasks to processors which better exploits the hardware resources in order to improve performance. In this paper we argue that the benefits of heterogeneous CMPs are bolstered by the usage of a dynamic assignment policy, i.e., a runtime mechanism which observes the behavior of the running threads and exploits thread migration between the cores. We validate our analysis by means of simulation. Specifically, our model assumes a combination of Alpha EV5 and Alpha EV6 processors and of integer and floating point programs from the SPEC2000 benchmark suite. We show that a dynamic assignment can outperform a static one by 20% to 40% on average and by as much as 80% in extreme cases, depending on the degree of multithreading simulated.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Michela Becchi: colleagues
Patrick Crowley: colleagues