Correlated Data Streaming
Tuesday December 7, 2004
Hamerschlag Hall D-210
Carnegie Mellon University
Effective data prefetching requires accurate mechanisms to predict
both which cache blocks to prefetch and when to
prefetch them. Recent research advocates using last-touch predictors
to both identify the last access to a cache block prior to eviction
and prefetch a replacement. Unfortunately, current last-touch predictors
and prefetchers are impractical because they store stand-alone prediction
signatures in on-chip associative structures and require storage
proportional to a program's memory footprint.
In this talk, I will present two last-touch predictors. First,
I will review the Dead-Block Correlating Prefetcher, a previously
proposed last-touch predictor that requires very large on-chip storage
to be effective. Second, I will introduce Last-Touch Correlated
Data Streaming (LT-CORDS), a practical design for data streaming
that leverages the benefits of last-touch predictors while offloading
the large predictor signature storage to off-chip DRAM.
Mike is a first year PhD student in the Computer Architecture
Laboratory at Carnegie Mellon, where he is advised by Prof. Babak
Falsafi. His time has primarily been devoted to researching DBCP
and constructing LT-CORDS. His research interests include processors
and anything that relates to them.