Sharma Rahul, Gupta Nitin, Narang Vipin, Mittal Ankush
Department of Computer Science and Engineering, College of Engineering Roorkee, India.
Int J Bioinform Res Appl. 2011;7(2):202-15. doi: 10.1504/IJBRA.2011.040097.
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.
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。
