Parallel DNA Sequence Alignment on the Cell Broadband Engine

Wirawan, Adrianto; Keong, Kwoh Chee; Schmidt, Bertil

doi:10.1007/978-3-540-68111-3_132

Cited by 15 publications

(10 citation statements)

References 6 publications

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“…Li et al [40] also proposed a single-GPU implementation of the SW algorithm for long DNA sequences, but did not yield as fast speed as either CUDAlign or SW#. In addition, Wirawan et al [41] proposed the use of a Cell/BE for long DNA sequence alignments, and Zhao et al [42] utilized Streaming SIMD Extensions 2 (SSE2) vector instructions to implement an open-source library, named SSW, for genomic sequence alignment.…”

Section: Introductionmentioning

confidence: 98%

SWAPHI-LS: Smith-Waterman Algorithm on Xeon Phi coprocessors for Long DNA Sequences

Liu

Tran

Lauenroth

et al. 2014

2014 IEEE International Conference on Cluster Computing (CLUSTER)

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As an optimal method for sequence alignment, the Smith-Waterman (SW) algorithm is widely used. Unfortunately, this algorithm is computationally demanding, especially for long sequences. This has motivated the investigation of its acceleration on a variety of high-performance computing platforms. However, most work in the literature is only suitable for short sequences. In this paper, we present SWAPHI-LS, the first parallel SW algorithm exploiting emerging Xeon Phi coprocessors to accelerate the alignment of long DNA sequences. In SWAPHI-LS, we have investigated three parallelization approaches (naïve, tiled, and distributed) in order to deeply explore the inherent parallelism within Xeon Phis. To achieve high speed, we have explored two levels of parallelism within a single Xeon Phi and one more level of parallelism between Xeon Phis. Within a single Xeon Phi we exploit instruction-level parallelism within 512-bit single instruction multiple data (SIMD) instructions (vectorization) as well as thread-level parallelism over the many cores (multithreading). Between Xeon Phis we employ device-level parallelism in order to harness the compute power of Xeon Phi clusters (distributed computing based on the MPI offload model).The performance of our algorithm has been evaluated using a variety of genome sequences of lengths ranging from 4.4 million to 50 million nucleotides. Our performance evaluation reveals that our implementation achieves a stable performance of up to 30.1 billion cell updates per second (GCUPS) on a single Xeon Phi and up to 111.4 GCUPS on four Xeon Phis sharing the same host. SWAPHI-LS is written in C++ (with a set of SIMD intrinsics), OpenMP and MPI. The source code is publicly available at http://swaphi-ls.sourceforge.net.

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Section: Introductionmentioning

confidence: 98%

SWAPHI-LS: Smith-Waterman Algorithm on Xeon Phi coprocessors for Long DNA Sequences

Liu

Tran

Lauenroth

et al. 2014

2014 IEEE International Conference on Cluster Computing (CLUSTER)

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“…The Cell BE [6,8,11] is a recently introduced single-chip heterogeneous multi-core processor, which has been jointly developed by Sony, Toshiba and IBM. Previous work on parallelizing sequence analysis applications on the Cell BE focused on DP-based algorithms such as Smith-Waterman and HMMer [12,14]. Compared to these highly regular applications, parallelization of BLASTP is more challenging since it consists of a pipeline of computations with different memory and processing requirements.…”

Section: Introductionmentioning

confidence: 99%

Accelerating BLASTP on the Cell Broadband Engine

Zhang

Schmidt

Müller‐Wittig

2008

Pattern Recognition in Bioinformatics

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Abstract. The enormous growth of biological sequence databases has caused bioinformatics to be rapidly moving towards a data-intensive, computational science. As a result, the computational power needed by bioinformatics applications is growing rapidly as well. The recent emergence of low cost parallel accelerator technologies has made it possible to reduce execution times of many bioinformatics applications. In this paper, we demonstrate how the PlayStation®3, powered by the Cell Broadband Engine, can be used as an efficient computational platform to accelerate the popular BLASTP algorithm.

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“…We also provide some clues about the kind of program modifications that would be required to take advantage of a Cell-based system. For the interested reader, in the literature we can find several references about accelerating Evolutionary Algorithms on the Cell [4,29,2] and on graphics processing units (GPUs) [10,30].…”

Section: Introductionmentioning

confidence: 99%

Evaluating the cell broadband engine as a platform to run estimation of distribution algorithms

Pérez-Miguel

Miguel-Alonso

Mendiburu

2009

Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers

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Current consumer-grade computers and game devices incorporate very powerful processors that can be used to accelerate many classes of scientific codes. However, programming multi-core chips, hybrid multi-processors or graphical processing units is not an easy task for those programmers that deal mainly with sequential codes. In this paper, we explore the ability of the Cell Broadband Engine to run a particular Estimation of Distribution Algorithm. From an initial sequential version, we develop a multi-threaded one that is afterwards reworked to run on a Cell. The multi-threaded version is capable of efficiently use current multi-core chips, such as those used in desktop PCs. However, the efficiency of the Cell version is very low. We analyze the causes of these discouraging results, and provide some clues about the class of problems that could be efficiently ported to the Cell.

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Parallel DNA Sequence Alignment on the Cell Broadband Engine

Cited by 15 publications

References 6 publications

SWAPHI-LS: Smith-Waterman Algorithm on Xeon Phi coprocessors for Long DNA Sequences

SWAPHI-LS: Smith-Waterman Algorithm on Xeon Phi coprocessors for Long DNA Sequences

Accelerating BLASTP on the Cell Broadband Engine

Evaluating the cell broadband engine as a platform to run estimation of distribution algorithms

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