NDLI: Selective value prediction

Content Provider	ACM Digital Library
Author	Tullsen, Dean M. Calder, Brad Reinman, Glenn
Abstract	Value Prediction is a relatively new technique to increase instruction-level parallelism by breaking true data dependence chains. A value prediction architecture produces values, which may be later consumed by instructions that execute speculatively using the predicted value.This paper examines selective techniques for using value prediction in the presence of predictor capacity constraints and reasonable misprediction penalties. We examine prediction and confidence mechanisms in light of these constraints, and we minimize capacity conflicts through instruction filtering. The latter technique filters which instructions put values into the value prediction table. We examine filtering techniques based on instruction type, as well as giving priority to instructions belonging to the longest data dependence path in the processor's active instruction window. We apply filtering both to the producers of predicted values and the consumers. In addition, we examine the benefit of using different confidence levels for instructions using predicted values on the longest dependence path.
Starting Page	64
Ending Page	74
Page Count	11
File Format	PDF
ISBN	0769501702
DOI	10.1145/300979.300985
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1999-05-02
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Selective value prediction