Parallel Methods for Finding k-Mismatch Shortest Unique Substrings Using GPU

Abstract

k-mismatch shortest unique substring (SUS) queries have been proposed and studied very recently due to its useful 5 applications in the subfield of computational biology. The k-mismatch SUS query over one given position of a string asks for a shortest 6 substring that covers the given position and does not have a duplicate (within a Hamming distance of k) elsewhere in the string. The 7 challenge in SUS query is to collectively find the SUS for every position of a massively long string in a both time-and space-efficient 8 manner. All known efforts and results have been focused on improving and optimizing the time and space efficiency of SUS 9 computation in the sequential CPU model. In this work, we propose the first parallel approach for k-mismatch SUS queries, particularly 10 leveraging on the massive multi-threading architecture of the graphic processing unit (GPU) technology. Experimental study performed 11 on a mid-end GPU using real-world biological data shows that our proposal is consistently faster than the fastest CPU solution by a 12 factor of at least 6 for exact SUS queries (k ¼ 0) and at least 23 for approximate SUS queries over DNA sequences (k > 0), while 13 maintaining nearly the same peak memory usage as the most memory-efficient sequential CPU proposal. Our work provides 14 practitioners a faster tool for SUS finding on massively long strings, and indeed provides the first practical tool for approximate SUS 15 computation, because the any-case quadratical time cost of the state-of-the-art sequential CPU method for approximate SUS queries 16 does not scale well even to modestly long strings.

A k-mismatch string matching for generalized edit distance using diagonal skipping method

“…However, the overhead of control statements and reordered memory accesses is not considered for practical applications. The parallel string matching methods have been researched using the parallelism equipped in GPU (Graphics Processing Unit) [7,[16][17][18][19][20][21][22][23][24] and FPGA (Field Programmable Gate Array) [25][26][27][28][29], where the parallel programming requires multiple computational resources. However, sequential string matching based on a processing unit is still an attractive and fundamental topic in many practical applications.…”

More Time-Space Tradeoffs for Finding a Shortest Unique Substring

“…Hon et al gave an O(n 2 )-time, O(n)-space construction of an O(n)-space data structure, which, given q, in O(1) time returns the endpoints of a k-mismatch SUS for T[q]. Allen, Thankachan, and Xu [12] reduced the construction time to O(n log k n) at the cost of increasing the construction space to O(kn), and Schultz and Xu [13] gave a GPU algorithm that is fast in practice.…”