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Models of parallel computation: a survey and classification |
| ZHANG Yunquan1, CHEN Guoliang2, SUN Guangzhong2, MIAO Qiankun2 |
| 1.Laboratory of Parallel Computing, Institute of Software, Chinese Academy of Sciences, Beijing 100080, China; State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100080, China; 2.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 |
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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.
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Issue Date: 05 June 2007
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