Models of parallel computation :a survey and classification |
| |
Authors: | Zhang Yunquan Chen Guoliang Sun Guangzhong and Miao Qiankun |
| |
Affiliation: | (1) Laboratory of Parallel Computing, Institute of Software, Chinese Academy of Sciences, Beijing, 100080, China;(2) State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, 100080, China;(3) Anhui Province-MOST Key Co-Lab of High Performance Computing and Its Applications, Department of Computer Science and Technology, University of Science and Technology of China, Hefei, 230027, China |
| |
Abstract: | In this paper, the state-of-the-art parallel computational model research is reviewed. We will introduce various models that
were developed during the past decades. According to their targeting architecture features, especially memory organization,
we classify these parallel computational models into three generations. These models and their characteristics are discussed
based on three generations classification. We believe that with the ever increasing speed gap between the CPU and memory systems,
incorporating non-uniform memory hierarchy into computational models will become unavoidable. With the emergence of multi-core
CPUs, the parallelism hierarchy of current computing platforms becomes more and more complicated. Describing this complicated
parallelism hierarchy in future computational models becomes more and more important. A semi-automatic toolkit that can extract
model parameters and their values on real computers can reduce the model analysis complexity, thus allowing more complicated
models with more parameters to be adopted. Hierarchical memory and hierarchical parallelism will be two very important features
that should be considered in future model design and research. |
| |
Keywords: | parallel computational models hierarchical memory hierarchical parallelism three generations memory model |
本文献已被 万方数据 SpringerLink 等数据库收录! |
|