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Computer architectures continue to develop rapidly towards massively parallel and heterogeneous systems. Thus, easily extensible yet highly efficient parallelization approaches for a variety of platforms are urgently needed. In this paper, we present SWhybrid, a hybrid computing framework for large-scale biological sequence database search on heterogeneous computing environments with multi-core or...
PROSITE provides rich documentation entries describing protein domains, families and functional sites, associated patterns as well as generalized profiles to identify them. Generalized profiles in PROSITE are often used to detect distantly related proteins by doing sequence comparison. The developments of the PROSITE have increased the discriminatory power of generalized profiles. However in practice,...
In this paper we present XSW, a new parallel Smith-Waterman algorithm for searching protein sequence databases on the Xeon Phi coprocessor. In order to make full use of the compute power of the many-core Xeon Phi hardware, we have used a two-level parallelization scheme: the thread level coarse-grained and VPU level fine-grained parallelism to implement our algorithm. At the thread level, XSW employs...
MapReduce is a very popular programming model to support parallel and distributed large-scale data processing. There have been a lot of efforts to implement this model on commodity GPU-based systems. However, most of these implementations can only work on a single GPU. And they can not be used to process large-scale datasets. In this paper, we present a new approach to design the MapReduce framework...
Using modern graphics processing units for no-graphics high performance computing is motivated by their enhanced programmability, attractive price/performance ratio and incredible growth in speed. Although the pipeline of a modern graphics processing unit (GPU) permits high throughput and more concurrency, they bring more complexities in analyzing the performance of GPU-based applications. In this...
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