Big Data (BD) platforms have a long tradition of leveraging trends and technologies from the
broader computer network and communication community. For several years, dedicated …

In January 2019, the US Department of Energy, Office of Science program in Advanced
Scientific Computing Research, convened a workshop to identify priority research directions …

Research on in-memory big data management and processing has been prompted by the
increase in main memory capacity and the explosion in big data. By offering an efficient in …

Convergence between high-performance computing (HPC) and big data analytics (BDA) is
currently an established research area that has spawned new opportunities for unifying the …

Today's scientific applications are increasingly relying on a variety of data sources, storage
facilities, and computing infrastructures, and there is a growing demand for data analysis …

Because of their low cost, small size, low resources and self-organizing nature a Wireless
Sensor Network (WSN) is a potential solution in hostile environments including military …

Counting the abundance of all the distinct kmers in biological sequence data is a
fundamental step in bioinformatics. These applications include de novo genome assembly …

Big data frameworks are widely deployed in supercomputers for analyzing large-scale
datasets. Topological data processing is an emerging approach that focuses on analyzing …

K-mer counting is a fundamental operation in DNA research and genome analytics; its
application includes estimating genome assembly, understanding similarities in genomic …

MapReduce (MR) is a technique used to improve distributed data processing vastly and can
massively speed up computation. Hadoop and MR rely on memory-intensive JVM and Java …