Book Chapter10.1007/978-3-642-55195-6_23
Faster GPU-Accelerated Smith-Waterman Algorithm with Alignment Backtracking for Short DNA Sequences
Yongchao Liu,Bertil Schmidt +1 more
- 08 Sep 2013
- pp 247-257
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TL;DR: A GPU-accelerated Smith-Waterman (SW) algorithm with Alignment Backtracking, called GSWAB, for short DNA sequences that performs all-to-all pairwise alignments and retrieves optimal local alignments on CUDA-enabled GPUs.
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Abstract: In this paper, we present a GPU-accelerated Smith-Waterman (SW) algorithm with Alignment Backtracking, called GSWAB, for short DNA sequences. This algorithm performs all-to-all pairwise alignments and retrieves optimal local alignments on CUDA-enabled GPUs. To facilitate fast alignment backtracking, we have investigated a tile-based SW implementation using the CUDA programming model. This tiled computing pattern enables us to more deeply explore the powerful compute capability of GPUs. We have evaluated the performance of GSWAB on a Kepler-based GeForce GTX Titan graphics card. The results show that GSWAB can achieve a performance of up to 56.8 GCUPS on large-scale datasets. Furthermore, our algorithm yields a speedup of up to 53.4 and 10.9 over MSA-CUDA (the first stage) and gpu-pairAlign on the same hardware configurations.
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Citations
GateKeeper: a new hardware architecture for accelerating pre-alignment in DNA short read mapping.
TL;DR: GateKeeper is the first design to accelerate pre‐alignment using Field‐Programmable Gate Arrays (FPGAs), which can perform pre-alignment much faster than software, and maintains high accuracy while providing 90‐fold and 130‐fold speedup over the state‐of‐the‐art software pre‐Alignment techniques, Adjacency Filter and Shifted Hamming Distance (SHD), respectively.
•Posted Content
GateKeeper: Enabling Fast Pre-Alignment in DNA Short Read Mapping with a New Streaming Accelerator Architecture.
TL;DR: The main idea of GateKeeper is to filter out the incorrect mappings in a streaming fashion using Field-Programmable Gate Arrays (FPGAs) at an early stage, which reduces the number of candidate verifications in the rest of the execution, and thus accelerate the read mapping.
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GSWABE: faster GPU-accelerated sequence alignment with optimal alignment retrieval for short DNA sequences
Yongchao Liu,Bertil Schmidt +1 more
TL;DR: This work investigates a general tile‐based approach to facilitating fast alignment by deeply exploring the powerful compute capability of CUDA‐enabled GPUs and presents GSWABE, a graphics processing unit (GPU)‐accelerated pairwise sequence alignment algorithm for a collection of short DNA sequences.
SWAPHI-LS: Smith-Waterman Algorithm on Xeon Phi coprocessors for Long DNA Sequences
Yongchao Liu,Tuan Tu Tran,Felix Lauenroth,Bertil Schmidt +3 more
- 01 Sep 2014
TL;DR: SWAPHI-LS is presented, the first parallel SW algorithm exploiting emerging Xeon Phi coprocessors to accelerate the alignment of long DNA sequences and achieves a stable performance of up to 30.1 billion cell updates per second on a single Xeon Phi and up to 111.4 GCUPS on four Xeon Phis sharing the same host.
MAGNET: Understanding and Improving the Accuracy of Genome Pre-Alignment Filtering
TL;DR: MAGNET is proposed, a new filtering strategy that maintains high accuracy across different edit distance thresholds and data sets and significantly improves the accuracy of pre-alignment filtering by one to two orders of magnitude.
References
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