Title :
GPU-accelerated Burrow-Wheeler Transform for genomic data
Author :
Zhiheng Zhao ; Jianping Yin ; Wei Xiong
Author_Institution :
Sch. of Comput. Sci., Nat. Univ. of Defense Technol., Changsha, China
Abstract :
As the core of FM-index and compressed suffix array, the Burrows-Wheeler Transform (BWT) plays a key role in indexing genomic sequence data for pattern search. It is more space-efficient than suffix tree and suffix array and also has good searching performance. However, computing a BWT from a sequence in efficient space and time is challenging. In this article, we present a fast algorithm for computing BWT which leverages the computing power of graphics processing unit (GPU). It is based on a blockwise suffix sorting method which builds BWT block-by-block and uses a GPU to accelerate the suffix sorting procedures. Our GPU-accelerated algorithm only needs small memory space and experiments show that it is about 16 times faster than the original CPU implementation for computing BWT of human whole genome.
Keywords :
data compression; genomics; graphics processing units; indexing; information retrieval; sequences; sorting; wavelet transforms; BWT; Burrows-Wheeler transform; FM index; GPU accelerated algorithm; blockwise suffix sorting method; compressed suffix array; genomic sequence data indexing; graphics processing unit; memory space; pattern search; Burrows-Wheeler Transform; GPU; suffix array;
Conference_Titel :
Biomedical Engineering and Informatics (BMEI), 2012 5th International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-1183-0
DOI :
10.1109/BMEI.2012.6513199