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在GPU架构上使用PWM并行实现DNA序列匹配算法

Parallel implementation of DNA sequences matching algorithms using PWM on GPU architecture.

作者信息

Sharma Rahul, Gupta Nitin, Narang Vipin, Mittal Ankush

机构信息

Department of Computer Science and Engineering, College of Engineering Roorkee, India.

出版信息

Int J Bioinform Res Appl. 2011;7(2):202-15. doi: 10.1504/IJBRA.2011.040097.

Abstract

Positional Weight Matrices (PWMs) are widely used in representation and detection of Transcription Factor Of Binding Sites (TFBSs) on DNA. We implement online PWM search algorithm over parallel architecture. A large PWM data can be processed on Graphic Processing Unit (GPU) systems in parallel which can help in matching sequences at a faster rate. Our method employs extensive usage of highly multithreaded architecture and shared memory of multi-cored GPU. An efficient use of shared memory is required to optimise parallel reduction in CUDA. Our optimised method has a speedup of 230-280x over linear implementation on GPU named GeForce GTX 280.

摘要

位置权重矩阵(PWMs)被广泛用于表示和检测DNA上的转录因子结合位点(TFBSs)。我们在并行架构上实现了在线PWM搜索算法。大量的PWM数据可以在图形处理单元(GPU)系统上并行处理,这有助于以更快的速度匹配序列。我们的方法大量使用了高度多线程的架构和多核GPU的共享内存。在CUDA中,需要有效地使用共享内存来优化并行归约。我们的优化方法在名为GeForce GTX 280的GPU上比线性实现有230 - 280倍的加速。

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