Last-touch correlated data streaming

Recent research advocates address-correlating predictors to identify cache block addresses for prefetch. Unfortunately, address-correlating predictors require correlation data storage proportional in size to a program's active memory footprint. As a result, current proposals for this class of predictor are either limited in coverage due to constrained on-chip storage requirements or limited in prediction lookaheaddue to long off-chip correlation data lookup. In this paper, we propose Last-Touch Correlated Data Streaming (LT-cords), a practical address-correlating predictor. The key idea of LT-cords is to record correlation data off chip in the order they will be used and stream them into a practicallysized on-chip table shortly before they are needed, thereby obviating the need for scalable on-chip tables and enabling low-latency lookup. We use cycle-accurate simulation of an 8-way out-of-order superscalar processor to show that: (1) LT-cords with 214KB of on-chip storage can achieve the same coverage as a last-touch predictor with unlimited storage, without sacrificing predictor lookahead, and (2) LT-cords improves performance by 60% on average and 385% at best in the benchmarks studied. © 2007 IEEE.

Published in:
Proceedings of the International Symposium on Performance Analysis of Systems and Software, 105 - 115
Presented at:
San Jose, CA, April

 Record created 2009-04-06, last modified 2018-03-17

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