Git Product home page Git Product logo

gpu-bsw's Introduction

ADEPT Revamped

A newer, more user friendly version of ADEPT is available here. It is recommended to use the newer version unless you are trying to reproduce the results from the original ADEPT paper.

ADEPT (GPU-BSW)

GPU-BSW or GPU Batch Smith-Waterman is a GPU accelerated implementation of the Smith-Waterman alignment algorithm based on the ADEPT strategy hence also referenced as ADEPT. Implementation details of ADEPT can be found in the publication here: https://rdcu.be/b7fhY. ADEPT uses GPU's two level parallelism to perform multiple sequence alignments in batches while using fine grained parallelism to accelerate each individual alignment. Overall it provides several time faster performance in comparison to existing SIMD implementations for CPU, a comparative study with existing CPU and GPU methods has been provided in the publication mentioned above. ADEPT performs a complete smith-waterman alignment with affine gap penalities and can align both protein and DNA sequences.

ADEPT provides a driver function that separates CUDA code from the main application which enables easy use and integeration in existing applications, effectively providing a drop in replacement for CPU libraries. The driver also enables balancing of alignments across all the GPUs available on a system.

To Build:

mkdir build

cd build

cmake CMAKE_BUILD_TYPE=Release ..

make

To Execute DNA test run:

./program_gpu dna ../test-data/dna-reference.fasta ../test-data/dna-query.fasta ./out_file

To Execute Protein test run:

./program_gpu aa ../test-data/protein-reference.fasta ../test-data/protein-query.fasta ./out_file

Contact

If you need help modifying the library to match your specific use-case or for other issues and bug reports please open an issue or reach out at [email protected]

Citation

Awan, M.G., Deslippe, J., Buluc, A. et al. ADEPT: a domain independent sequence alignment strategy for gpu architectures. BMC Bioinformatics 21, 406 (2020). https://doi.org/10.1186/s12859-020-03720-1

License:

GPU accelerated Smith-Waterman for performing batch alignments (GPU-BSW) Copyright (c) 2019, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved.

If you have questions about your rights to use or distribute this software, please contact Berkeley Lab's Intellectual Property Office at [email protected].

NOTICE. This Software was developed under funding from the U.S. Department of Energy and the U.S. Government consequently retains certain rights. As such, the U.S. Government has been granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the Software to reproduce, distribute copies to the public, prepare derivative works, and perform publicly and display publicly, and to permit other to do so.

gpu-bsw's People

Contributors

mgawan avatar r-barnes avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.