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Selecting long atomic traces for high coverage
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Source International Conference on Supercomputing archive
Proceedings of the 17th annual international conference on Supercomputing table of contents
San Francisco, CA, USA
SESSION: Processor microarchitecture I table of contents
Pages: 2 - 11  
Year of Publication: 2003
ISBN:1-58113-733-8
Authors
Roni Rosner  Microprocessor Research Intel Labs (formerly MRL), Haifa, Israel
Micha Moffie  Microprocessor Research Intel Labs (formerly MRL), Haifa, Israel
Yiannakis Sazeides  University of Cyprus, Nicosia, Cyprus
Ronny Ronen  Microprocessor Research Intel Labs (formerly MRL), Haifa, Israel
Sponsors
ACM: Association for Computing Machinery
SIGARCH: ACM Special Interest Group on Computer Architecture
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 4,   Downloads (12 Months): 20,   Citation Count: 4
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ABSTRACT

This paper performs a comprehensive investigation of dynamic selection for long atomic traces. It introduces a classification of trace selection methods and discusses existing and novel dynamic selection approaches - including loop unrolling, procedure in-lining and incremental merging of traces based on dynamic bias. The paper empirically analyzes a number of selection schemes in an idealized framework.Observations based on the SPEC-CPU2000 benchmarks show that: (a) selection based on dynamic bias is necessary to achieve the best performance across all benchmarks, (b) the best selection scheme is benchmark and maximum trace-length specific, (c) simple selection, based on program structure information only, is sufficient to achieve the best performance for several benchmarks.Consequently, two alternatives for the trace selection mechanism are established: (a) a "best performance" approach relying on complex dynamic criteria; (b) a "value" approach that provides the best performance (and potentially the best power consumption) based on simpler static criteria. Another emerging alternative advocates adaptive based mechanisms to adjust selection criteria.


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:
Roni Rosner: colleagues
Micha Moffie: colleagues
Yiannakis Sazeides: colleagues
Ronny Ronen: colleagues