A heterogeneous computing system for data mining workflows in multi-agent environments
✍ Scribed by Ping Luo; Kevin Lü; Rui Huang; Qing He; Zhongzhi Shi
- Book ID
- 111060465
- Publisher
- John Wiley and Sons
- Year
- 2006
- Tongue
- English
- Weight
- 277 KB
- Volume
- 23
- Category
- Article
- ISSN
- 0266-4720
No coin nor oath required. For personal study only.
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An important problem in heterogeneous computing (HC) is predicting task execution time. A methodology is introduced for determining the execution time distribution for a given data parallel program that is to be executed in an SIMD, MIMD (SPMD), and/or mixed-mode SIMD/MIMD (SPMD) HC environment. The
Multi-Agent Intelligent Systems (MAIS) are loosely-coupled network of problem solving systems that, whenever needed, work together with each other to dynamically solve problems that none of the system can individually solve. Among the advantages of the MAIS, when compared to the centralized systems,