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Scientific applications vs. SPEC-FP: a comparison of program behavior
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Source International Conference on Supercomputing archive
Proceedings of the 20th annual international conference on Supercomputing table of contents
Cairns, Queensland, Australia
SESSION: Benchmarking and modeling table of contents
Pages: 66 - 74  
Year of Publication: 2006
ISBN:1-59593-282-8
Authors
Kyle Rupnow  Univ. of Wisconsin, Madison, WI and Sandia National Labs, Albuquerque, NM
Arun Rodrigues  Univ. of Notre Dame, Notre Dame, IN
Keith Underwood  Sandia National Labs, Albuquerque, NM
Katherine Compton  Univ. of Wisconsin, Madison, WI
Sponsors
SIGARCH: ACM Special Interest Group on Computer Architecture
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Many modern scientific applications execute on massively parallel collections of microprocessors. Supercomputers such as the Cray XT3 (Red Storm) and Blue Gene/L support thousands to tens of thousands of processors per parallel job. However, individual microprocessor performance remains a critical component of overall performance. Traditional approaches to improve scientific application performance concentrate on floating-point (FP) instructions; however, our studies show that in the scientific applications used at Sandia National Labs, integer instructions constitute a large and critical part of the instruction mix. Although the SPEC-FP benchmark suite is considered representative of FP workloads, it has a much smaller proportion of integer computation instructions than the Sandia scientific applications, with 22.9% as compared to 36.9%. Integer instructions in Sandia applications also behave differently than in SPEC-FP. Integer instruction outputs are reused 8.8x to 13.1x more often in SPEC-FP benchmarks, and integer dataflow in Sandia applications is more complex than in the SPEC-FP suite. In this work, we examine common dataflow and usage patterns of integer instructions---information essential to develop hardware techniques to accelerate critical scientific applications. We present statistics for SPEC-FP and Sandia applications, summarizing integer computation usage and the size, shape and interface (number of inputs/outputs) of dataflow graphs.


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:
Kyle Rupnow: colleagues
Arun Rodrigues: colleagues
Keith Underwood: colleagues
Katherine Compton: colleagues