NDLI: Quantifying Instruction Criticality

Content Provider	ACM Digital Library
Author	Tullsen, Dean M. Calder, Brad Tune, Eric
Abstract	Information about instruction criticality can be used to control the application of micro-architectural resources efficiently. To this end, several groups have proposed methods to predict critical instructions. This paper presents a framework that allows us to directly measure the criticality of individual dynamic instructions. This allows us to (1) measure the accuracy of proposed critical path predictors, (2) quantify the amount of slack present in non-critical instructions, and (3) provide a new metric, called tautness, which ranks critical instructions by their dominance on the critical path. This research investigates methods for improving critical path predictor accuracy and studies the distribution of slack and tautness in programs. It shows that instruction criticality changes dynamically, and that criticality history patterns can be used to significantly improve predictor accuracy.
ISBN	0769516203
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2002-09-22
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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Quantifying Instruction Criticality