Title :
Study on GPU-accelerated extraction of interconnects parasitic using CUDA and MPI
Author :
Xu, Xiaoyu ; Liu, Guoqiang ; Qu, Hui ; Xu, Wei ; Zhang, Yang
Author_Institution :
Inst. of Electr. Eng., Chinese Acad. of Sci., Beijing, China
Abstract :
Parallel computation is application-oriented, particularly for the GPU (Graphics Processing Unit) with the inherent parallelism. This paper shows the architecture of a GPU cluster based on MPI (Message Passing Interface) and CUDA (Compute Unified Device Architecture). Results show that the acceleration ratio is obviously improved but the acceleration effect seems decelerated in large-scale GPU cluster. The parallel algorithm is mainly focused on task partitioning sparse matrix-vector multiplications (SpVM) in GPUs.
Keywords :
matrix multiplication; message passing; microprocessor chips; parallel architectures; sparse matrices; CUDA; GPU cluster architecture; GPU-accelerated extraction; MPI; acceleration effect; acceleration ratio; compute unified device architecture; graphics processing unit; interconnects parasitic; large-scale GPU cluster; message passing interface; parallel algorithm; parallel computation; sparse matrix-vector multiplication; task partitioning; Acceleration; Computer applications; Computer architecture; Computer interfaces; Concurrent computing; Graphics; Large-scale systems; Message passing; Parallel algorithms; Parallel processing;
Conference_Titel :
Electromagnetic Field Computation (CEFC), 2010 14th Biennial IEEE Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4244-7059-4
DOI :
10.1109/CEFC.2010.5481435
