1. SPM management using markov chain based data access prediction
- Author
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Srikantaiah, Kandemir, Ozturk, and Yemliha
- Subjects
Compiler analysis ,Paper ,Industrial management ,Dynamic prediction ,Computer science ,Embedded systems ,Program compilers ,Markov process ,Integrated circuits ,computer.software_genre ,symbols.namesake ,Data accesses ,Maximum performances ,System on a chip ,Statistical process control ,Static random-access memory ,Dynamic predictions ,Self phase modulation ,Application programs ,Markov chain ,Markov chains ,Computer aided design ,Markov processes ,Management techniques ,Management schemes ,Access patterns ,Memory management ,Data access ,symbols ,Data mining ,Scalar values ,computer ,Optimizing compilers ,Scratchpad memories - Abstract
Date of Conference: 10-13 Nov. 2008 Conference name: 2008 IEEE/ACM International Conference on Computer-Aided Design 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%.
- Published
- 2008