Type of Document Master's Thesis Author Ahmed, Nova Author's Email Address novaahmed@hotmail.com URN etd-12062004-140624 Title Parallel Algorithm for Memory Efficient Pairwise and Multiple Genome Alignment in Distributed Environment Degree Master of Science Department Computer Science Advisory Committee
Advisor Name Title Dr. Yi Pan Committee Chair Dr. A. P. Preethy Committee Member Dr. Saeid Belkasim Committee Member Keywords
- pairwise sequence alignment
- multiple sequence alignment
- parallel algorithm
- memory efficient pairwise alignment
Date of Defense 2004-11-05 Availability restricted Abstract The genome sequence alignment problems are very important ones from the computational biology perspective. These problems deal with large amount of data which is memory intensive as well as computation intensive.
In the literature, two separate algorithms have been studied and improved – one is a Pairwise sequence alignment algorithm which aligns pairs of genome sequences with memory reduction and parallelism for the computation and the other one is the multiple sequence alignment algorithm that aligns multiple genome sequences and this algorithm is also parallelized efficiently so that the workload of the alignment program is well distributed.
The parallel applications can be launched on different environments where shared memory is very well suited for these kinds of applications. But shared memory environment has the limitation of memory usage as well as scalability also these machines are very costly. A better approach is to use the cluster of computers and the cluster environment can be further enhanced to a grid environment so that the scalability can be improved introducing multiple clusters. Here the grid environment is studied as well as the shared memory and cluster environment for the two applications. It can be stated that for carefully designed algorithms the grid environment is comparable for its performance to other distributed environments and it sometimes outperforms the others in terms of the limitations of resources the other distributed environments have.
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