Bio:Chongke Bi, received the B.Sc. (Eng.) degree and the M.Sc. (Eng.) degree from Shandong University, China, in 2004 and 2007, respectively, and the Ph.D. (Sci.) degree from the University of Tokyo, Japan, in 2012. After that, as a researcher in RIKEN, Japan, he was focus on the research in the field of visual analysis of big data on supercomputer from 2012 to 2016. He is currently in Tianjin University. His current research interests include big data, visualization, image processing, and computer graphics.
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Abstract: The development of supercomputers has successfully helped us to carry on complicated simulation with exploded size of dataset. For visualizing such kind of large-scale dataset, reducing the data size by using compression methods is one of the most useful approach. Moreover, parallelization of compression algorithm can greatly improve the efficiency and resolve the limitation of memory size. However, in parallel compression algorithm, interprocessor communication is indispensable, while it is also a bottleneck problem, especially for the general cases that the number of processors is not power-of-two. I will introduce our 2-3-4 combination approach, which can be simply implemented and also reach high performance of parallel computing algorithms. Furthermore, our method can obtain the best balance among all parallel computing processors. This is achieved by transferring the non-power-of-two problem into power-of-two problem to fully use the best balance feature of binary swap method. The method has been evaluated on the K computer. |
