Title :
Predicting data cache misses in non-numeric applications through correlation profiling
Author :
Mowry, Todd C. ; Luk, Chi-Keung
Author_Institution :
Dept. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
To maximize the benefit and minimize the overhead of software-based latency tolerance techniques. We 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
Keywords :
cache storage; instruction sets; microprogramming; program compilers; software performance evaluation; cache miss profiling technique; correlation profiling; data cache miss prediction; dynamic references; intermediate miss ratios; latency hiding; memory stall time; nonnumeric applications; software-based latency tolerance; summary profiling; Application software; Art; Computer science; Data analysis; Delay; Information analysis; Prefetching; Processor scheduling; Registers;
Conference_Titel :
Microarchitecture, 1997. Proceedings., Thirtieth Annual IEEE/ACM International Symposium on
Conference_Location :
Research Triangle Park, NC
Print_ISBN :
0-8186-7977-8
DOI :
10.1109/MICRO.1997.645827