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Finite Element Analysis Model for Assessing Expansion Patterns from Surgically Assisted Rapid Palatal Expansion

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An efficient and high performance linear recursive variable expansion implementation of the Smith-Waterman algorithm.

Laiq Hasan¹, Zaid Al-Ars

¹Delft University of Technology,The Netherlands. L.HASAN@EWI.TUDELFT.NL

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|December 8, 2009

Summary

This summary is machine-generated.

We developed a faster linear recursive variable expansion (RVE) method for the Smith-Waterman (S-W) algorithm. This new approach significantly improves performance over traditional methods, despite using more computational resources.

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Area of Science:

Bioinformatics
Computer Science
Algorithm Optimization

Background:

The Smith-Waterman algorithm is crucial for sequence alignment in bioinformatics.
Traditional implementations, like linear systolic arrays, face performance limitations.
Efficient algorithm design is key for handling large biological datasets.

Purpose of the Study:

To introduce and evaluate a novel linear recursive variable expansion (RVE) implementation of the Smith-Waterman (S-W) algorithm.
To compare the performance and resource utilization of the RVE approach against traditional linear systolic array implementations.
To demonstrate the potential of RVE for accelerating sequence alignment tasks.

Main Methods:

Implementation of the Smith-Waterman algorithm using a linear recursive variable expansion (RVE) technique.
Development of a traditional linear systolic array implementation for comparative analysis.
Performance benchmarking and resource utilization assessment of both implementations.

Main Results:

The linear RVE implementation achieved performance improvements of up to 2.33 times compared to the linear systolic array.
The enhanced performance of the RVE method came at the cost of approximately doubling the resource utilization.
The study quantifies the trade-off between speed and resource consumption for the RVE approach.

Conclusions:

The linear RVE implementation offers a significant performance boost for the Smith-Waterman algorithm.
RVE presents a viable alternative for accelerating sequence alignment when increased resource usage is acceptable.
Further research can explore resource optimization strategies for RVE-based Smith-Waterman implementations.