New Shape Analysis and Interprocedural Techniques for Automatic Parallelization of C Codes

Authors:
Francisco Corbera;Rafael Asenjo;Emilio Zapata
Affiliations:
Computer Architecture Department, University of Malaga, Complejo Politecnico, Campus de Teatinos, Apdo. 4114, E-29080 Malaga, Spain. corbera@ac.uma.es;Computer Architecture Department, University of Malaga, Complejo Politecnico, Campus de Teatinos, Apdo. 4114, E-29080 Malaga, Spain. asenjo@ac.uma.es;Computer Architecture Department, University of Malaga, Complejo Politecnico, Campus de Teatinos, Apdo. 4114, E-29080 Malaga, Spain. ezapata@ac.uma.es
Venue:
International Journal of Parallel Programming
Year:
2002

Citing 11
Cited 1

Direct methods for sparse matrices

Direct methods for sparse matrices
Detecting conflicts between structure accesses

PLDI '88 Proceedings of the ACM SIGPLAN 1988 conference on Programming Language design and Implementation
Dependence analysis for pointer variables

PLDI '89 Proceedings of the ACM SIGPLAN 1989 Conference on Programming language design and implementation
Analysis of pointers and structures

PLDI '90 Proceedings of the ACM SIGPLAN 1990 conference on Programming language design and implementation
A general data dependence test for dynamic, pointer-based data structures

PLDI '94 Proceedings of the ACM SIGPLAN 1994 conference on Programming language design and implementation
Alias analysis of pointers in Pascal and Fortran 90: dependence analysis between pointer references

Acta Informatica
Solving shape-analysis problems in languages with destructive updating

ACM Transactions on Programming Languages and Systems (TOPLAS)
New shape analysis techniques for automatic parallelization of C codes

ICS '99 Proceedings of the 13th international conference on Supercomputing
Loop Transformations for Restructuring Compilers: The Foundations

Loop Transformations for Restructuring Compilers: The Foundations
Parallelizing Programs with Recursive Data Structures

IEEE Transactions on Parallel and Distributed Systems
Analysis of Dynamic Structures for Efficient Parallel Execution

Proceedings of the 6th International Workshop on Languages and Compilers for Parallel Computing

An extended ANSI C for processors with a multimedia extension

International Journal of Parallel Programming

Quantified Score

Hi-index	0.00

Visualization

Abstract

Automatic parallelization of codes with complex data structures is becoming very important. These complex, and often recursive, data structures are widely used in scientific computing. Shape analysis is one of the key steps in the automatic parallelization of such codes. In this paper we extend the Static Shape Graph (SSG) method to enable the successful and accurate detection of complex doubly-linked structures. We have also included an interprocedural analysis in our framework. These techniques have been implemented in a compiler, which has been validated for several C codes. In particular, we present the results the compiler achieves for the C sparse LU factorization algorithm and for a recursive code generating a tree data structure. The output SSG perfectly describes the complex data structure used in these codes.