Code Optimizations for Parallelization of Programs using Data Dependence Identifier

In a Parallelizing Compiler, code transformations help to reduce the data dependencies and identify parallelism in a code. In our earlier paper, we proposed a model Data Dependence Identifier (DDI), in which a program P is represented as graph GP . Using ??? , we could identify data dependencies in...

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Bibliographic Details
Published in:International journal of advanced computer science & applications Vol. 12; no. 10
Main Authors: Alluru, Kavya, L, Jeganathan
Format: Journal Article
Language:English
Published: West Yorkshire Science and Information (SAI) Organization Limited 01.01.2021
Subjects:
Algorithms
Computer science
Graph representations
Graphical representations
Polynomials
Privatization
Transformations
Variables
ISSN:2158-107X, 2156-5570
Online Access:Get full text
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Summary:In a Parallelizing Compiler, code transformations help to reduce the data dependencies and identify parallelism in a code. In our earlier paper, we proposed a model Data Dependence Identifier (DDI), in which a program P is represented as graph GP . Using ??? , we could identify data dependencies in a program and also perform transformations like dead code elimination and constant propagation. In this paper, we present algorithms for loop invariant code motion, live range analysis, node splitting and loop fusion code transformations using DDI in polynomial time.
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ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2021.0121093