Intelligent solid-state drives (iSSDs) allow execution of limited application functions (eg, data
filtering or aggregation) on their internal hardware resources, exploiting SSD characteristics …

The Changing Paradigm of Data-Intensive Computing Page 1 erogeneous full-scale
simulations will require not only petaflop capabilities but also a computational infrastructure that …

With the recent advances in Remote Sensing (RS) techniques, continuous Earth
Observation is generating tremendous volume of RS data. The proliferation of RS data is …

The distributed file system, HDFS, is widely deployed as the bedrock for many parallel big
data analysis. However, when running multiple parallel applications over the shared file …

针对煤矿瓦斯灾害的特点, 提出了用粗糙集理论对瓦斯灾害进行预测. 分析了瓦斯灾害特征,
并建立了瓦斯灾害特征知识库, 应用粗糙集理论建立了煤矿瓦斯灾害预测的数据挖掘模型 …

In this paper, we study parallel data access on distributed file systems, eg, the Hadoop file
system. Our experiments show that parallel data read requests are often served data …

The resurgence of current and upcoming multithreaded architectures and programming
models led us to conduct a detailed study to understand the potential of these platforms to …

Class-attribute interdependence maximization (CAIM) is one of the state-of-the-art
algorithms for discretizing data for which classes are known. However, it may take a long …

With data volumes increasing at a high rate and the emergence of highly scalable
infrastructures (cloud computing, petascale computing), distributed management of data …

In this chapter, we present the convergence analysis and applications of particle swarm
optimization algorithm. Although it is difficult to analyze the convergence of this algorithm …