Proceedings Article10.1109/SASP.2010.5521145
Accelerating DNA analysis applications on GPU clusters
Antonino Tumeo,Oreste Villa +1 more
- 13 Jun 2010
- pp 71-76
44
TL;DR: This paper presents an efficient implementation of the Aho-Corasick algorithm for high performance clusters accelerated with Graphic Processing Units (GPUs) and compares this implementation to MPI and MPI with pthreads based implementations for a homogeneous cluster of x86 processors.
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Abstract: DNA analysis is an emerging application of high performance bioinformatics. Modern sequencing machinery are able to provide, in few hours, large input streams of data which needs to be matched against exponentially growing databases of known fragments. The ability to recognize these patterns effectively and fastly may allow extending the scale and the reach of the investigations performed by biology scientists. Aho-Corasick is an exact, multiple pattern matching algorithm often at the base of this application. In this paper we present an efficient implementation of the Aho-Corasick algorithm for high performance clusters accelerated with Graphic Processing Units (GPUs). We discuss how we partitioned and adapted the algorithm to fit the Tesla C1060 GPU and then present a MPI based implementation for a heterogeneous high performance cluster. We compare this implementation to MPI and MPI with pthreads based implementations for a homogeneous cluster of x86 processors, discussing the stability vs. the performance and the scaling of the solutions, taking into consideration aspects such as the bandwidth among the different nodes.
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Citations
5PM: secure pattern matching
Joshua W. Baron,Karim El Defrawy,Kirill Minkovich,Rafail Ostrovsky,Eric Tressler +4 more
- 05 Sep 2012
TL;DR: The techniques reduction pattern matching and generalized Hamming distance problem to a novel linear algebra formulation that allows for generic solutions based on any additively homomorphic encryption are believed to be of independent interest.
5PM: Secure pattern matching
TL;DR: The problem of secure pattern matching that allows single-character wildcards and substring matching in the malicious stand-alone setting is considered and the first secure expressive pattern matching protocol designed to optimize round complexity by carefully specifying the entire protocol round by round is considered.
State-of-the-Art GPGPU Applications in Bioinformatics
Nikitas Papangelopoulos,Dimitrios Vlachakis,Arianna Filntisi,Paraskevas Fakourelis,Louis Papageorgiou,Vasileios Megalooikonomou,Sophia Kossida +6 more
- 01 Oct 2013
TL;DR: A comprehensive review of available bioinformatics tools ranging from sequence and image analysis to protein structure prediction and systems biology that use NVIDIA Compute Unified Device Architecture CUDA general-purpose computing on graphics processing units GPGPU programming language is presented.
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Efficient parallel automata construction for hybrid resource-impelled data-matching
TL;DR: This approach represents the first known hybrid-parallel model for the construction of such automata and the first to allow self-adjusting pattern-matching automata in real-time by allowing full-duplex transfers at maximum throughput between the host (CPU) and the device (GPU).
15
Memory Efficient Parallelization for Aho-Corasick Algorithm on a GPU
Nhat-Phuong Tran,Myungho Lee,Sugwon Hong,Minho Shin +3 more
- 25 Jun 2012
TL;DR: A new memory efficient parallelization technique is presented which efficiently places and caches the input text data and the reference data in the on-chip shared memories and texture caches of the Graphic Processing Unit (GPU).
12
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