SWAMP Align - Shannon Steinfadt

SWAMP

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Smith-Waterman and ASC

boxPushing the boundaries of current computing and alignment approaches for faster and better sequence alignment, SWAMP is leading the way. Using the high-sensitivity approach first utilized by Smith-Waterman, SWAMP or Smith-Waterman using Associative Massive Parallelism, is a suite of algorithms designed for the high-performance parallel model known as ASC.

SWAMP and SWAMP+ use innovative and creative techniques to maximize the algorithms' efficiency, designed to take advantage of ASC's strengths.

This library of algorithms have been developed with bioinformatics and sequence alignment users in mind, by may be applicable to many diverse area where approximate string matching is necessary.

These algorithms are ideal for allowing a user to find and customize subsequent local alignments. This can be used in finding motifs, regulatory regions and other in-depth bioinformatics studies where the exact results and sensitivity of the Smith-Waterman like computations are necessary. These algorithms allow for an in-depth study between two sequences in an automated way that does not currently exist.

Got Sequences? We Need Your Input!

SWAMP+ takes advantage of the associative paradigm for algorithm development, but lacks commercial hardware support for that model.

boxOne goal of my research is to create mainstream application software that runs the SWAMP+ suite of algorithms on commercially available hardware. To do this, ASC’s associative functionality has to be efficiently emulated on commercial hardware. This is important since the functions necessary that run ASC code should not degrade the overall performance to the point of negating the advantages gained through the use parallelism.  Please contact me to participate in a very short questionnaire.

 

Updates

October 2013

For those of you attending the Grace Hopper Celebration of Women in Computing in Minneapolis, MN, there will be a poster session on the sequence alignment work called "Beyond the Data SWAMP: Parallel Paradigms for Large Scale Sequence Alignment." In addition, Shannon will be giving a talk entitled "Gaming the System: Gamification for Nuclear and High-Hazard Response Training"

September 2013

Journal paper published and available online “Fine-Grained Parallel Implementations for SWAMP+ Smith-Waterman Alignment,” Shannon Irene Steinfadt. J. of Parallel Computing. Available online 4 September 2013, ISSN 0167-8191, http://dx.doi.org/10.1016/j.parco.2013.08.008.

March 2012

Filed United States Patent Application 13/423,085: “Computer-Facilitated Parallel Information Alignment and Analysis.” This patent outlines approaches for an extended Smith-Waterman genomic data sequence alignment algorithm used for finding similarities in data strings that can discover multiple sub-string alignments efficiently on parallel computing architectures.

March 2010

Shannon defended the Ph.D. dissertation Smith-Waterman Sequence Alignment for Massively Parallel High-Performance Computing Architectures.

November 2009

If you are attending Supercomputing SC'09 conference, stop by to visit Shannon at the ACM Student Research Poster Competition. The poster is titled Large-Scale Wavefront Parallelization on Multiple Cores for Sequence Alignment. She is the recipient of the Broader Engagement Grant for SC for the second year.

September 2009

Invited speaker for the CRA-W Workshop at Grace Hopper Celebration of Women in Computing - The Road to Graduate School

Shannon started a Graduate Research Assistantship at Los Alamos National Lab with the Decision and Risk Anaylsis, continuing her research with parallel and HPC Smith-Waterman sequence alignment.

June 2009

Shannon held a summer position at Los Alamos National Laboratory with the Performance and Architectures Lab.  She spent the summer looking at performance metric and parallel algorithms on several architectures, including SSE intrinsics and JumboMem.

Shannon Steinfadt and Kevin Schaffer had a paper that appeared in the 4th Ohio Collaborative Conference for Bioinformatics (OCCBIO), Cleveland, Ohio, June 15-17, 2009 “Parallel Approaches for SWAMP Sequence Alignment.”

 

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