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DecGPU: distributed error correction on massively parallel graphics processing units using CUDA and MPI

10 years 6 months ago
DecGPU: distributed error correction on massively parallel graphics processing units using CUDA and MPI
Background: Next-generation sequencing technologies have led to the high-throughput production of sequence data (reads) at low cost. However, these reads are significantly shorter and more error-prone than conventional Sanger shotgun reads. This poses a challenge for the de novo assembly in terms of assembly quality and scalability for large-scale short read datasets. Results: We present DecGPU, the first parallel and distributed error correction algorithm for high-throughput short reads (HTSRs) using a hybrid combination of CUDA and MPI parallel programming models. DecGPU provides CPUbased and GPU-based versions, where the CPU-based version employs coarse-grained and fine-grained parallelism using the MPI and OpenMP parallel programming models, and the GPU-based version takes advantage of the CUDA and MPI parallel programming models and employs a hybrid CPU+GPU computing model to maximize the performance by overlapping the CPU and GPU computation. The distributed feature of our algor...
Yongchao Liu, Bertil Schmidt, Douglas L. Maskell
Added 12 May 2011
Updated 12 May 2011
Type Journal
Year 2011
Where BMCBI
Authors Yongchao Liu, Bertil Schmidt, Douglas L. Maskell
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