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Welcome to the BarraCUDA Project page

Started in 2009, the aim of the BarraCUDA project is to develop a sequence mapping software that utilizes the massive parallelism of graphics processing units (GPUs) to accelerate the inexact alignment of short sequence reads to a particular location on a reference genome.

BarraCUDA can align a paired-end library containing 14 million pairs of 76bp reads to the Human genome in about 27 minutes (from fastq files to SAM alignment) using a 380 NVIDIA Geforce GTX 680*. The alignment throughput can be boosted further by using multiple GPUs (up to 8) at the same time.

Being based on BWA (http://bio-bwa.sf.net) from the Sanger Institute, BarraCUDA delivers a high level of alignment fidelity and is comparable to other mainstream alignment programs. It can perform gapped alignment with gap extensions, in order to minimise the number of false variant calls in re-sequencing studies.

Software Features

    • NVIDIA CUDA accelerated FM-index inexact alignment algorithm
    • Supports gapped alignment with gap extensions
    • Top of the class alignment fidelity
    • Outputs in popular SAM format for downstream analyses
    • Speed equivalent to 10-15 Intel Xeon cores (per GPU*)
    • NEW! SamPE command now supports POSIX multithreading
    • Supports up to 8x concurrent GPUs in one host computer
    • Supports mainstream NVIDIA Geforce, Quadro and Tesla graphics cards
    • NVIDIA GeForce GTX680 (4GB), Tesla C20XX and Quadro 6000 are recommended for large genomes
  • Citations

    Please cite the following two papers when you use BarraCUDA:

      Klus P, Lam S, Lyberg D, Cheung MS, Pullan G, McFarlane I, Yeo GSH, Lam BY. (2012) BarraCUDA - a fast short read sequence aligner using graphics processing units. BMC Research Notes, 5:27. [PMID: 22244497]

      Li H and Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler Transform. Bioinformatics, 25:1754-60. [PMID: 19451168]

    * Measured using a NVIDIA GeForce GTX680 and an Intel Xeon X5660 Processor. The timings were based on the time taken for aligning the two libraries (-aln command) and also outputting in SAM format (-sampe command) Last updated: 24 Oct 2012

    What's New

    BarraCUDA (R260) is now compatible with CUDA 5.0 and the new Kepler K10 GPUs

    GeForce GTX680 offers a 20% boost in alignment throughput compared to a Tesla C2075

    The new 'manyfish' script provide users an easy way to use multiple GPUs and outputs .SAI files.

    The alignment throughputs of 1 to 8x Tesla C2050s compared to equal number of x86 cores. (Klus et al., 2012)
    The alignment throughputs of 0.6.1 vs 0.6.2. With 2 GPUs and a 6-core processor, 0.6.2 can align 1M 70bp reads in about one minute.
    The fast mode does not have any great effect on the percentage of mappings and the alignment accuracy.

    The command line screenshot.

    BarraCUDA outputs in popular SAM format for downstream analyses.

    A comparison with alignments generated by BWA and MAQ.