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Improving memory system performance with energy-efficient value speculation
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Source ACM SIGARCH Computer Architecture News archive
Volume 33 ,  Issue 4  (November 2005) table of contents
Special issue: dasCMP'05
COLUMN: Regular contributions table of contents
Pages: 121 - 127  
Year of Publication: 2005
ISSN:0163-5964
Authors
Nana B. Sam  Cornell University, Ithaca, NY
Martin Burtscher  Cornell University, Ithaca, NY
Publisher
ACM  New York, NY, USA
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ABSTRACT

Microprocessor speeds have been improving much faster than memory speeds, resulting in the CPU spending a larger and larger amount of time waiting for data. Processor designers have employed several ways to improve memory performance, including hierarchical caching, prefetching, and faster memory chips. Yet, memory accesses still represent a major performance bottleneck and much remains to be done to tolerate the increasing memory latencies. Load-value prediction has been shown to effectively hide some of this latency. However, the hardware required to achieve good performance is substantial, making load-value prediction unappealing in light of increasing power constraints. In this paper, we present a novel predictor that significantly increases CPU performance while at the same time decreasing the energy consumption of the entire processor relative to a baseline with a well-performing hybrid load-value predictor.


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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R. Bhargava, L. K. John. Performance and Energy Impact of Instruction-Level Value Predictor Filtering. First Value-Prediction Workshop, 2003, pp. 71--78.
 
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G. H. Loh. Width-Partitioned Load Value Predictors. Journal of Instruction-Level Parallelism, 2003, pp. 1--23.
 
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N. B. Sam, M. Burtscher. Exploiting Type Information in Load-Value Predictors. Second Value-Prediction and Value-Based Optimization Workshop, 2004, pp. 32--39.
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Collaborative Colleagues:
Nana B. Sam: colleagues
Martin Burtscher: colleagues