4.2 Article

High-performance short sequence alignment with GPU acceleration

Journal

DISTRIBUTED AND PARALLEL DATABASES
Volume 30, Issue 5-6, Pages 385-399

Publisher

SPRINGER
DOI: 10.1007/s10619-012-7099-x

Keywords

Sequence alignment; GPGPU; Parallel systems

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Sequence alignment is a fundamental task for computational genomics research. We develop G-Aligner, which adopts the GPU as a hardware accelerator to speed up the sequence alignment process. A leading CPU-based alignment tool is based on the Bi-BWT index; however, a direct implementation of this algorithm on the GPU cannot fully utilize the hardware power due to its irregular algorithmic structure. To better utilize the GPU hardware resource, we propose a filtering-verification algorithm employing both the Bi-BWT search and direct matching. We further improve this algorithm on the GPU through various optimizations, e.g., the split of a large kernel, the warp based implementation to avoid user-level synchronization. As a result, G-Aligner outperforms another state-of-the-art GPU-accelerated alignment tools SOAP3 by 1.8-3.5 times for in-memory sequence alignment.

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