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Implementation and evaluation of a migration-based NUCA design for chip multiprocessors
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Joint International Conference on Measurement and Modeling of Computer Systems archive
Proceedings of the 2008 ACM SIGMETRICS international conference on Measurement and modeling of computer systems table of contents
Annapolis, MD, USA
POSTER SESSION: Posters table of contents
Pages 449-450  
Year of Publication: 2008
ISBN:978-1-60558-005-0
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Authors
Feihui Li  NVIDIA, Santa Clara, CA, USA
Mahmut Kandemir  The Pennsylvania State University, University Park, PA, USA
Mary J. Irwin  The Pennsylvania State University, University Park, PA, USA
Sponsors
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Chip Multiprocessors (CMPs) and Non-Uniform Cache Architectures (NUCAs) represent two emerging trends in computer architecture. Targeting future CMP based systems with NUCA type L2 caches, this paper proposes a novel data migration algorithm for parallel applications and evaluates it. The goal of this migration scheme is to determine a suitable location for each data block within a large L2 space at any given point during execution. A unique characteristic of the proposed scheme is that it models the problem of optimal data placement in the L2 cache space as a two dimensional post office placement problem, presents a practical architectural implementation of this model, and gives an evaluation of the proposed implementation.


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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S. Borkar et al. Platform 2015: Intel processor and platform evolution for the next decade. Technology@Intel Magazine, Mar. 2005.
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Standard Performance Evaluation Corporation. SPEC OMP. http://www.spec.org/hpg/omp2001/, Dec. 2005.
 
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Standard Performance Evaluation Corporation. SPECWEB http://www.spec.org/web2005/

Collaborative Colleagues:
Feihui Li: colleagues
Mahmut Kandemir: colleagues
Mary J. Irwin: colleagues