In the Big Data era, the gap between the storage performance and an application's I/O
requirement is increasing. I/O congestion caused by concurrent storage accesses from …

Managing software packages in a scientific computing environment is a challenging task,
especially in the case of heterogeneous systems. It is error prone when installing and …

Data‐driven programming models such as many‐task computing (MTC) have been
prevalent for running data‐intensive scientific applications. MTC applies over …

According to exascale computing roadmap, the dynamic nature of new generation scientific
problems needs an undergoing review in the static management of computing resources …

Data driven programming models like MapReduce have gained the popularity in large-scale
data processing. Although great efforts through the Hadoop implementation and framework …

This paper presents a convergence of distributed key‐value storage systems in clouds and
supercomputers. It specifically presents ZHT, a zero‐hop distributed key‐value store system …

Supercomputers, nowadays, aggregate a large number of nodes featuring the same
nominal HW components (eg, processors and GPGPUS). In real-life machines, the chips …

Processors with 100s of threads of execution are among the state-of-the-art in high-end
computing systems. This transition to many-core computing has required the community to …

MICE tourism has received the attention and support from relevant departments and tourism
industry with the growth rate of recent years. In this paper, the dynamics mechanism of urban …

Resource discovery in distributed Exascale computing systems, in addition to managing
events resulting in failures due to not finding the resource, as well as failure to perform …