Paper Info
Title
Predicting data cache misses in non-numeric applications through correlation profiling
Abstract
To maximize the benefit and minimize the overhead of software-based latency tolerance techniques, we would like to apply them precisely to the set of dynamic references that suffer cache misses. Unfortunately, the information provided by the state-of-the-art cache miss profiling technique (summary profiling) is inadequate for references with intermediate miss ratios - it results in either failing to hide latency, or else inserting unnecessary overhead. To overcome this problem, we propose and evaluate a new technique - correlation profiling - which improves predictability by correlating the caching behavior with the associated dynamic context. Our experimental results demonstrate that roughly half of the 22 non-numeric applications we study can potentially enjoy significant reductions in memory stall time by exploiting at least one of the three forms of correlation profiling we consider.
Year
DOI
Venue
1997
10.1109/MICRO.1997.645827
MICRO
Keywords
Field
DocType
software-based latency tolerance technique,state-of-the-art cache,non-numeric application,unnecessary overhead,profiling,cache miss prediction,correlation,dynamic reference,predicting data cache,latency tolerance.,correlation profiling,non-numeric applications,summary profiling,dynamic context,new technique,caching behavior,computer science,compilers,information analysis,software engineering,art,instruction sets,application software,microprogramming,registers,data management,performance engineering,data analysis
Microcode,Computer science,Cache,Profiling (computer programming),Latency (engineering),Instruction set,Parallel computing,Real-time computing,Compiler,Software,Application software
Conference
ISSN
ISBN
Citations 
1072-4451
0-8186-7977-8
30
PageRank 
References 
Authors
4.30
13
2
Name
Order
Citations
PageRank
Todd C. Mowry13021253.75
Chi-Keung Luk22537116.49