A data locality optimizing algorithm
PLDI '91 Proceedings of the ACM SIGPLAN 1991 conference on Programming language design and implementation
Global optimizations for parallelism and locality on scalable parallel machines
PLDI '93 Proceedings of the ACM SIGPLAN 1993 conference on Programming language design and implementation
Data and computation transformations for multiprocessors
PPOPP '95 Proceedings of the fifth ACM SIGPLAN symposium on Principles and practice of parallel programming
Maximizing parallelism and minimizing synchronization with affine transforms
Proceedings of the 24th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
APL '98 Proceedings of the APL98 conference on Array processing language
High-level Language Support for User-defined Reductions
The Journal of Supercomputing
MPI: A Message-Passing Interface Standard
MPI: A Message-Passing Interface Standard
OpenMP extensions for generic libraries
IWOMP'08 Proceedings of the 4th international conference on OpenMP in a new era of parallelism
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In this paper, a parallel programming algorithm for DNA sequence alignment on multi-core processor architectures is proposed. We discuss the issues involved in implementation of aligning genome sequences using global sequence alignment algorithm and parallelizing them using tiling and OpenMP on multicore architecture. Sequence alignment is a fundamental instrument in Bioinformatics. In recent years, numerous proposals have been addressed the problem of accelerating this class of applications. In this paper we focus on the analysis of the alignment in global algorithm, a widely used program for performing multiple sequence alignment. We have parallelized global algorithm on multi-core architecture and have carefully analyzed the scalability of its different phases with both the number of cores used and the input size. Our experimental results illustrate that by selecting appropriate tile size for different architecture and for different input size, total parallel execution time is significantly reduced. The developed computing system is implemented on the PC-based Linux cluster with different multicore architecture.