Paper Info
Title
SPM management using Markov chain based data access prediction
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%.
Year
DOI
Venue
2008
10.1109/ICCAD.2008.4681632
San Jose, CA
Keywords
Field
DocType
Markov processes,SRAM chips,embedded systems,information retrieval,program compilers,Markov chain,SPM management,SRAM,affine subscript functions,compiler analysis,data access prediction,dynamic prediction,embedded systems,indexed array accesses,pointer accesses,scratchpad memories
Affine transformation,Pointer (computer programming),Markov process,Computer science,Markov chain,Parallel computing,Compiler,Real-time computing,Optimizing compiler,Memory management,Data access
Conference
ISSN
ISBN
Citations 
1092-3152 E-ISBN : 978-1-4244-2820-5
978-1-4244-2820-5
5
PageRank 
References 
Authors
0.44
21
4
Name
Order
Citations
PageRank
Taylan Yemliha1363.76
Shekhar Srikantaiah221510.47
Mahmut T. Kandemir37371568.54
ozcan ozturk419117.42