GPU-Friendly Parallel Genome Matching with Tiled Access and Reduced State Transition Table

In this paper, we propose a new parallel genome matching algorithm using graphics processing units (GPUs). Our proposed approach is based on the Aho–Corasick algorithm and it was developed based on a consideration of the architectural features of existing GPUs with a hundred or more cores. Thus, we...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:International journal of parallel programming Ročník 41; číslo 4; s. 526 - 551
Hlavní autori: Oh, Yunho, Oh, Doohwan, Ro, Won W.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Boston Springer US 01.08.2013
Springer Nature B.V
Predmet:
Algorithms
Analysis
Computer programming
Computer Science
Data transfer (computers)
Genomes
Graphics boards
Keywords
Matching
Parallel processing
Partitioning
Pattern recognition systems
Performance enhancement
Processor Architectures
Software Engineering/Programming and Operating Systems
Studies
Tables (data)
Tasks
Theory of Computation
Parallel processing
Graphics processors
Concurrent programming
Pattern matching
ISSN:0885-7458, 1573-7640
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:In this paper, we propose a new parallel genome matching algorithm using graphics processing units (GPUs). Our proposed approach is based on the Aho–Corasick algorithm and it was developed based on a consideration of the architectural features of existing GPUs with a hundred or more cores. Thus, we provide an appropriate task partitioning method that runs on multiple threads and we fully utilize the cache memory and the shared memory structures available in GPUs. Especially, we propose a tiled access method for rapid data transfer from the global memory to the shared memory. We also provide new models for cache-friendly state transition table to improve performance of pattern matching operations on GPUs. The maximum throughput we achieved in various experiments was 15.3 Gbps. Moreover, we showed that our proposed design outperformed an earlier approach with a 15.4 % performance improvement.
Bibliografia:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-1
ObjectType-Feature-2
content type line 23
ISSN:0885-7458
1573-7640
DOI:10.1007/s10766-012-0234-5