Title :
Improve simulation efficiency using statistical benchmark subsetting - An implantbench case study
Author :
Jin, Zhanpeng ; Cheng, Allen C.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Pittsburgh, Pittsburgh, PA
Abstract :
Motivated by excessively high benchmarking efforts caused by rapidly expanding design space and prevailing practices based on ad-hoc and subjective schemes, this paper seeks to improve simulation efficiency by proposing a novel methodology that combines two statistical analyses and one quantitative heuristic capable of subsetting a given benchmark suite based on the targeted processor configuration and desired variance coverage. We demonstrate the usage and effectiveness of the proposed technique by conducting a thorough case study on ImplantBench suite evaluating high/mid/low-end machine configurations modeled after three commercial embedded processors.
Keywords :
benchmark testing; statistical analysis; ImplantBench; ad-hoc schemes; commercial embedded processors; improve simulation efficiency; processor configuration; quantitative heuristic; statistical analyses; statistical benchmark subsetting; subjective schemes; variance coverage; Analytical models; Biomedical measurements; Clustering algorithms; Computational modeling; Computer simulation; Microarchitecture; Permission; Space exploration; Statistical analysis; Statistics; Benchmark; Cluster; Multivariate statistical analysis; Subset;
Conference_Titel :
Design Automation Conference, 2008. DAC 2008. 45th ACM/IEEE
Conference_Location :
Anaheim, CA
Print_ISBN :
978-1-60558-115-6