机群系统中矩阵的并行QR分解算法

随着高速网络技术的快速发展，机群系统已经成为并行计算的主要平台，由于它的高通信延迟，某些在并行机上实现的细粒度并行算法己不适合在该环境下运行，为此有必要研究它们在机群系统中的并行实现。基于这一点，本文对矩阵的QR分解提出了一种新的任务划分策略，并由此得到了它的一种粗粒度并行算法。实验结果表明，设计的并行算法在机群系统中具有较高的加速比。

Parallel algorithm of QR decomposition of matrix in cluster system

With the rapid development of high-speed network technology, the cluster systems have been the main platform of parallel algorithm. Because their high communication delay, some parallel algorithms of fine grain are not fit to run in this environment. Therefore, it is necessary to study their parallel achievements in cluster systems. In terms of that, a new way for QR decomposition of matrix is proposed and coarse grain parallel algorithms is obtained in this paper. The example shows that the designing parallel algorithm has more higher speedup ratio in this cluster systerms.