원문정보
보안공학연구지원센터(IJGDC)
International Journal of Grid and Distributed Computing
Vol.9 No.11
2016.11
pp.143-156
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
In cloud computing era, automatic parallelization is still significant for virtualization platform. However, after several decades of development, the overall effect is still to be improved. Summary of the mainstream technology developments will be beneficial to reveal the future direction and trend. This paper reviews the technology of loop parallelization, which is the key issue in automatic parallelization. After introducing the basic models and approaches, we focus on the recent developments, on which we obtain the trend of this field and the conclusions about future.
목차
Abstract
1. Introduction
2. Polyhedral Model and Affine Transformations
2.1 Data Dependence Analysis
2.3. Loop Transformation
2.4. Code Generation
3. Graph Theory Based Models and Partitions
4. Semantics, Stencil and High Level Abstract
5. Dynamic Analysis and Scheduling
5.1. The Use of Compile Time Information
5.2. The Dynamic Scheduling
5.3. Pipeline Parallelization
5.4. Speculative Parallelization
6. Intelligent Algorithms
7. Conclusion and Future Trend
References
1. Introduction
2. Polyhedral Model and Affine Transformations
2.1 Data Dependence Analysis
2.3. Loop Transformation
2.4. Code Generation
3. Graph Theory Based Models and Partitions
4. Semantics, Stencil and High Level Abstract
5. Dynamic Analysis and Scheduling
5.1. The Use of Compile Time Information
5.2. The Dynamic Scheduling
5.3. Pipeline Parallelization
5.4. Speculative Parallelization
6. Intelligent Algorithms
7. Conclusion and Future Trend
References
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자료제공 : 네이버학술정보