Paper Info
Title
Loop transformations for reducing data space requirements of resource-constrained applications
Abstract
Embedded computing platforms are often resource constrained, requiring great design and implementation attention to memory, power and heat related parameters. An important task for a compiler in such platforms is to simplify the process of developing applications for limited memory devices and resource constrained clients. Focusing on array-intensive embedded applications, this work explores how loop-based compiler optimizations can be used for increasing memory location reuse. Our goal is to transform a given application in such a way that the resulting code has fewer cases (as compared to the original code) where the lifetimes of array elements overlap. The reduction in lifetimes of array elements can then be exploited by reusing memory locations as much as possible. Our results indicate that the proposed strategy reduces data space requirements of ten resource constrained applications by more than 40% on the average.
Year
DOI
Venue
2003
10.1007/3-540-44898-5_22
SAS
Keywords
Field
DocType
resource-constrained application,array-intensive embedded application,loop-based compiler optimizations,array element,original code,limited memory device,reusing memory location,loop transformation,data space requirement,memory location reuse,fewer case,resulting code,compiler optimization,embedded computing
Data space,Computer science,Reuse,Embedded applications,Optimizing compiler,Real-time computing,Compiler,Array element,Iteration space,Distributed computing
Conference
Volume
ISSN
ISBN
2694
0302-9743
3-540-40325-6
Citations 
PageRank 
References 
5
0.46
15
Authors
5
Name
Order
Citations
PageRank
Priya Unnikrishnan120014.67
Guangyu Chen221118.96
Mahmut T. Kandemir37371568.54
Mustafa Karakoy4374.11
Ibrahim Kolcu527020.83