Mikhail Zymbler^*, Alexander Grents, Yana Kraeva, Sachin Kumar

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1867-1878, 2021, DOI:10.32604/cmc.2020.014232

Abstract A discord is a refinement of the concept of an anomalous subsequence of a time series. Being one of the topical issues of time series mining, discords discovery is applied in a wide range of real-world areas (medicine, astronomy, economics, climate modeling, predictive maintenance, energy consumption, etc.). In this article, we propose a novel parallel algorithm for discords discovery on high-performance cluster with nodes based on many-core accelerators in the case when time series cannot fit in the main memory. We assumed that the time series is partitioned across the cluster nodes and achieved parallelization among the cluster nodes as… More >

Lili He^{1, 2}, Zhiwei Cai^{1, 2}, Dantong Ouyang^{1, 2}, Changshuai Wang^{1, 2}, Yu Jiang^{1, 2}, Chong Wang^{1, 2, 3}, Hongtao Bai^{1, 2, *}

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 373-388, 2020, DOI:10.32604/cmc.2020.09860

Abstract In view of the satellite cloud-derived wind inversion has the characteristics of large scale, intensive computing and time-consuming serial inversion algorithm is very difficult to break through the bottleneck of efficiency. We proposed a parallel acceleration scheme of cloud-derived wind inversion algorithm based on MPI cluster parallel technique in this paper. The divide-and-conquer idea, assigning winds vector inversion tasks to each computing unit, is identified according to a certain strategy. Each computing unit executes the assigned tasks in parallel, namely divide-and-rule the inversion task, so as to reduce the efficiency bottleneck of long inversion time caused by serial time accumulation.… More >