Data-centered computing and implementation in web service
Chao Li, Lingda Wu, Bin Zhao · 2016
Parallel computer architectures bring synchronization problem which bog down the system. And the speed gap between CPU and memory keeps growing, making data operation more expensive. In some data-intensive applications, there are similar or coincident child operations in parallel threads, which take unnecessary resources. To effectively exploit parallelization, reduce the price of data operation, the concept of data-centered computing is proposed. By considering the similarity and relations between data and merging them into unions as threads' input, data-centered computing can eliminate data operation redundancy of data-intensive applications. An implementation in web service proves that data-centered computing can effectively improve performance.