Research Article
An Optimal Code Heuristic Approach for Compiler Optimization using Graph Coloring Technique
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 79 - Issue 1 |
| Published: October 2013 |
| Authors: Prateek Saraf, Rajnish Dashora |
10.5120/13708-1461
|
Prateek Saraf, Rajnish Dashora . An Optimal Code Heuristic Approach for Compiler Optimization using Graph Coloring Technique. International Journal of Computer Applications. 79, 1 (October 2013), 37-40. DOI=10.5120/13708-1461
@article{ 10.5120/13708-1461,
author = { Prateek Saraf,Rajnish Dashora },
title = { An Optimal Code Heuristic Approach for Compiler Optimization using Graph Coloring Technique },
journal = { International Journal of Computer Applications },
year = { 2013 },
volume = { 79 },
number = { 1 },
pages = { 37-40 },
doi = { 10.5120/13708-1461 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2013
%A Prateek Saraf
%A Rajnish Dashora
%T An Optimal Code Heuristic Approach for Compiler Optimization using Graph Coloring Technique%T
%J International Journal of Computer Applications
%V 79
%N 1
%P 37-40
%R 10.5120/13708-1461
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Graph theory has found its applications in various fields of computation involved in day to day life. A problem solving approach that incorporates graph theory has an added advantage of being simple and visually more comprehensible [9]. Data mining, image processing, astrology and astronomy, theoretical computer science, artificial intelligence and compiler optimization et al. , every evolving field utilizes efficient algorithms involving graphs and their properties. Graph coloring has major applications in the field of compiler optimization. This paper proposes a heuristic approach of graph coloring for code optimization and hence, improvement in compiler performance and accuracy. Color-based merging of colored graphs reduces the use of temporary variables, increasing efficiency in memory utilization. A comparative analysis has been carried out in order to present the advantages of the proposed algorithm [5] [6].
References
- Zhanju Cai, Alei Liang, Zhengwei Qi, Lingyan Jiang, Xiaolong Li, Haibing Guan, Ying Chen, Performance Comparison of Register Allocation Algorithms in Dynamic Binary Translation, International Conference on Knowledge and Systems Engineering, 2009.
- Ulrich Hirnschrott, Andreas Krall, and Bernhard Scholz, Graph Coloring vs. Optimal Register Allocation for Optimizing Compilers, Springer-Verlag Berlin Heidelberg ,2003.
- Istv´an Juhos, Jano I. van Hemert, Increasing the efficiency of graph coloring algorithms with a representation based on vector operations, Journal of Software, Vol1, No. 2, August, 2006.
- Ben A. Abderazek, Arquimedes Canedo and Masahiro Sowa, Quantitative Evaluation of Common Sub expression Elimination on Queue Machines, IEEE, 2008.
- Anjali Mahajan, M S Ali, Hybrid Evolutionary Algorithm for Graph Coloring Register Allocation, IEEE, 2008.
- David Karger, Rajeev Motwani, Madhu Sudan, Approximate Graph Coloring by Semidefinite Programming, IEEE, 1994.
- Monica S. Lam, Alfred V. Aho, Ravi Sethi, Jeffrey D. Ulman, Compilers: Principles, Techniques and Tools 2 Edition, Pearson 2008.
- Tommy R. Jensen, Graph Coloring Problems, John Wiley & Sons 1994.
- Narsingh Deo. Graph Theory with Applications to Engineering and Computer Science New Edition, PHI Learning 2009.
- Thomas H. Cormen, Charles E. Leiserson, Ronald L Rivest, Clifford Stein, Introduction To Algorithms, Mit Press (ma) 2009.
- Ashay Dharwadker, The Vertex Coloring Algorithm, Createspace 2011.
Index Terms
Keywords