You've made it to a portal for high performance parallel algorithms and adaptations for Smith-Waterman style sequence alignments. Thorough testing, fast speeds, and more information from your data. SWAMP Align.
What IS SWAMP?
SWAMP is the acronym for Smith-Waterman using Associative Massive Parallelism. The Smith-Waterman algorithm is a well-known and used local sequence alignment algorithm for aligning two strings (sequences) of genomic data. The idea is to discover similar (homologous) regions between the two sequences. SWAMP is a suite of algorithms that extend, parallelize, and optimize the basic approach that Smith-Waterman utilizes. Check out the SWAMP Page for more information.
Ask about asc
ASC is an associative computing model and the corresponding. The model is a single-instruction multiple data SIMD paradigm with several additional features designed to allow for fast, efficient searching based on content.
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.
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.
SWAMP is the acronym for Smith-Waterman using Associative Massive Parallelism. The Smith-Waterman algorithm is a well-known and used local sequence alignment algorithm for aligning two strings (sequences) of genomic data. The idea is to discover similar (homologous) regions between the two sequences. SWAMP is a suite of algorithms that extend, parallelize, and optimize the basic approach that Smith-Waterman utilizes. Check out the SWAMP Page for more information.