GPU-BLAST statistics

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Citations per year

Number of citations per year for the bioinformatics software tool GPU-BLAST
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Tool usage distribution map

This map represents all the scientific publications referring to GPU-BLAST per scientific context
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Associated diseases

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Popular tool citations

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Protocols

GPU-BLAST specifications

Information


Unique identifier OMICS_00995
Name GPU-BLAST
Alternative name Graphics Processing Unit - Basic Local Alignment Search Tool
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data Protein queries
Output data Alignment of protein sequences
Operating system Unix/Linux
Programming languages C++
Parallelization CUDA
Computer skills Advanced
Version 2.2.28
Stability Stable
Maintained Yes

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Documentation


Maintainer


  • person_outline Nick Sahinidis

Publication for Graphics Processing Unit - Basic Local Alignment Search Tool

GPU-BLAST citations

 (7)
library_books

Divide and Conquer (DC) BLAST: fast and easy BLAST execution within HPC environments

2017
PeerJ
PMCID: 5483034
PMID: 28652936
DOI: 10.7717/peerj.3486

[…] ectures of GPU cores (; ).A number of parallel BLAST applications have been developed, including GridBLAST (), CloudBLAST (), mpiBLAST (), HPC-BLAST (), PLAST (), ScalaBLAST (), a GPU-based BLAST (), GPU-BLAST (), and SCBI_MapReduce (). While these applications improve the execution time of BLAST, their compilation and configuration are complicated to varying degrees depending up on the libraries […]

library_books

Prefiltering Model for Homology Detection Algorithms on GPU

2016
Evol Bioinform Online
PMCID: 5170890
PMID: 28008220
DOI: 10.4137/EBO.S40877

[…] tween cost and performance. Our research and proposed implementation has focused on parallelizing BLAST with GPU hardware. At this point, either Liu et al. with CUDA-BLASTP, Vouzis and Sahinidis with GPU-BLAST, or Xiao et al. are based on the parallelization of all compute stages of NCBI BLAST. Following this reasoning, Liu et al. with CUDA-BLASTP evaluated the performance of their proposed algori […]

library_books

GPU Acceleration of Sequence Homology Searches with Database Subsequence Clustering

2016
PLoS One
PMCID: 4970815
PMID: 27482905
DOI: 10.1371/journal.pone.0157338

[…] , we mapped distance calculation, ungapped extension, and gapped extension of GHOSTZ onto a GPU. GHOSTZ-GPU with 2 GPUs is approximately 6 times faster than GHOSTZ with 2 CPU sockets. The accelerated GPU-BLAST and CUDA-BLASTP with 1 GPU are estimated to be equivalent to twice NCBI-BLAST with a single CPU socket or less [, ]. Therefore, GHOSTZ-GPU showed a greater increase in speed than GPU-based B […]

call_split

Comparison of Acceleration Techniques for Selected Low Level Bioinformatics Operations

2016
Front Genet
PMCID: 4748744
PMID: 26904094
DOI: 10.3389/fgene.2016.00005
call_split See protocol

[…] stems, distributing the input data to multiple computers as well.Additionally, adapted versions of BLAST running on special purpose hardware (FPGA: TimeLogic ®Tera-BLAST ™; TimeLogic Division, ; GPU: GPU-BLAST; Vouzis and Sahinidis, , G-BLASTN; Zhao and Chu, ) exist. […]

library_books

Exploiting GPUs in Virtual Machine for BioCloud

2013
Biomed Res Int
PMCID: 3654629
PMID: 23710465
DOI: 10.1155/2013/939460

[…] s to exploit GPUs. Manavski and Valle suggested a GPU implementation of Smith-Waterman sequence alignment [], and Vouzis and Sahinidis transformed the BLAST tool to a GPU based application, named the GPU-BLAST []. The barraCUDA [] and the G-aligner [] are also kinds of short sequence alignment tool with GPU acceleration. […]

library_books

Biodefense Oriented Genomic Based Pathogen Classification Systems: Challenges and Opportunities

2012
PMCID: 4289626
PMID: 25587492
DOI: 10.4172/2157-2526.1000113

[…] address the issue of speed, in the past firmware implementations of pairwise sequence homology algorithms have been reported as reconfigurable ASIC logic (TimeLogic BLAST), CUDA compatible GPU cards (GPU-BLAST) and reconfigurable computing Field Programmable Gate Arrays (FPGA-BLAST). While achieving an average of 20-fold speed accelerations over single CPU units, these methods are not suitable for […]


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GPU-BLAST institution(s)
Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA; Lane Center for Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA

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