Local DNA sequence alignment in a cluster of workstations: Algorithms and tools

Renata Cristina F Melo,Alba Cristina M A Melo,Rodolfo B Batista,Maria Emilia M T Walter,Marcelo N P Santana

doi:10.1007/bf03192360

Renata Cristina F Melo, Alba Cristina M A Melo + Show 3 more

Open Access

https://doi.org/10.1007/bf03192360

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Abstract

Abstract Distributed Shared Memory systems allow the use of the shared memory programming paradigm in distributed architectures where no physically shared memory exist. Scope consistent software DSMs provide a relaxed memory model that reduces the coherence overhead by ensuring consistency only at synchronization operations, on a per-lock basis. Much of the work in DSM systems is validated by benchmarks and there are only a few examples of real parallel applications running on DSM systems. Sequence comparison is a basic operation in DNA sequencing projects, and most of sequence comparison methods used are based on heuristics, that are faster but do not produce optimal alignments. Recently, many organisms had their DNA entirely sequenced, and this reality presents the need for comparing long DNA sequences, which is a challenging task due to its high demands for computational power and memory. In this article, we present and evaluate a parallelization strategy for implementing a sequence alignment algorithm for long sequences. This strategy was implemented in JIAJIA, a scope consistent software DSM system. Our results on an eight-machine cluster presented good speedups, showing that our parallelization strategy and programming support were appropriate.

Highlights

In order to make shared memory programming possible in distributed architectures, a shared memory abstraction must be created
In the shared memory programming paradigm, synchronization operations must be used every time processes want to restrict the order in which memory operations should be performed
The proposed parallel algorithm was implemented in C, using the software Distributed Shared Memory (DSM) JIAJIA v.2.1

Summary

Introduction

In order to make shared memory programming possible in distributed architectures, a shared memory abstraction must be created. It has been observed that providing such a strong memory consistency model creates a huge coherence overhead, slowing down the parallel application and bringing frequently the system into a thrashing state [10] To alleviate this problem, researchers have proposed to relax some consistency conditions, creating new shared memory behaviors that are different from the traditional uniprocessor one. In the shared memory programming paradigm, synchronization operations must be used every time processes want to restrict the order in which memory operations should be performed Using this fact, hybrid Memory Consistency Models guarantee that processors only have a consistent view of the shared memory at synchronization time [10]. For each similarity region, a global alignment is produced

Smith-Waterman’s Algorithm for DNA Sequence Alignment

Sequential Implementation

Distributed Shared Memory Systems

Parallel DNA Sequence Alignment

Experimental Results

Conclusion and Future Work