SPM management using markov chain based data access prediction
Author
Yemliha, T.
Srikantaiah, S.
Kandemir, M.
Öztürk, Özcan
Date
2008-11Source Title
IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
Publisher
IEEE
Pages
566 - 569
Language
English
Type
Conference PaperItem Usage Stats
140
views
views
97
downloads
downloads
Abstract
Leveraging the power of scratchpad memories (SPMs) available in most embedded systems today is crucial to extract maximum performance from application programs. While regular accesses like scalar values and array expressions with affine subscript functions have been tractable for compiler analysis (to be prefetched into SPM), irregular accesses like pointer accesses and indexed array accesses have not been easily amenable for compiler analysis. This paper presents an SPM management technique using Markov chain based data access prediction for such irregular accesses. Our approach takes advantage of inherent, but hidden reuse in data accesses made by irregular references. We have implemented our proposed approach using an optimizing compiler. In this paper, we also present a thorough comparison of our different dynamic prediction schemes with other SPM management schemes. SPM management using our approaches produces 12.7% to 28.5% improvements in performance across a range of applications with both regular and irregular access patterns, with an average improvement of 20.8%.
Keywords
Access patternsApplication programs
Compiler analysis
Data accesses
Dynamic predictions
Management schemes
Management techniques
Markov chains
Maximum performances
Optimizing compilers
Scalar values
Scratchpad memories
Computer aided design
Embedded systems
Industrial management
Integrated circuits
Markov processes
Paper
Program compilers
Statistical process control
Self phase modulation