Paper Info
Title
Accurate off-line phase classification for HW/SW co-designed processors
Abstract
Evaluation techniques in microprocessor design are mostly based on simulating selected application's samples using a cycle-accurate simulator. These samples usually correspond to different phases of the application stream. To identify these phases, relevant high-level application statistics are collected and clustered using a process named \"Off-Line Phase Classification\". The purpose of phase classification is to reduce the number of samples that need to be simulated with the minimum loss in accuracy (compared to simulating the complete set of samples). Unfortunately, when directly applied to HW/SW co-designed processors the traditional phase classifications do not provide a good trade-off between accuracy and the number of samples. As an example, according to our experimental results, to achieve a 4% error (compared to simulating all the samples) one needs to simulate 2.5X more samples for the case of HW/SW co-designed processors compared to what is necessary for HW-only processors. In this paper, we propose a novel off-line phase classification scheme called TOL Description Vector (TDV), which is suitable for HW/SW co-designed processors. TDV targets at estimating the TOL particularities and on average gives significantly better accuracy than traditional phase classification for any number of selected samples. For instance, TDV reaches the average error of 3% with 3X less samples than traditional classification. These benefits apply for different TOL and microarchitecture configurations.
Year
DOI
Venue
2014
10.1145/2597917.2597937
Conf. Computing Frontiers
Keywords
Field
DocType
hw/sw co-designed processors,design studies,simulation,warm-up methodology,dynamic binary translation,performance
Off line,Computer science,Classification scheme,Parallel computing,Real-time computing,Microprocessor design,Microarchitecture
Conference
Citations 
PageRank 
References 
0
0.34
21
Authors
4
Name
Order
Citations
PageRank
Aleksandar Brankovic100.34
Kyriakos Stavrou21038.61
Enric Gibert3877.85
Antonio González43178229.66