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The demands of data analysis and processing make the parallel computing platforms are continuously developed. But the existing parallel computing models which are the core of platforms present the characteristics of diversification, high pertinence and short cycle. So a synthetic model of supporting flexible platforms urgently needs to be researched. This work researches a synthetic model to shield the heterogeneity of parallel computing models under the theories of λ -calculus, functional language and graph reduction. Based on the MapReduce and BSP models, first of all, the performing principles of models are analyzed. And then the unified modalities of models are found. Finally, the synthetic model having high performance is developed with graph reduction rules, and the experiment results are also shown.

The Research of Synthesizing Parallel Computing Models with Graph Reduction