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This Chapter focuses on the differences between control parallelism and data parallelism, which are important to understand the discussion about parallel data mining in later Chapters of this book. After an introduction to control and data parallelism, we discuss the effect of exploiting these two kinds of parallelism in three important issues, namely easy of use, machine-architecture independence and scalability. Then we discuss the related issues of data partitioning and data placement, which form the basis for the exploitation of data parallelism.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |