Two major trends in computing systems are the growth in high performance computing
(HPC) with in particular an international exascale initiative, and big data with an …

With the ever-increasing need to analyze large amounts of data to get useful insights, it is
essential to develop complex parallel machine learning algorithms that can scale with data …

Data‐driven applications are essential to handle the ever‐increasing volume, velocity, and
veracity of data generated by sources such as the Web and Internet of Things (IoT) devices …

The dawn of exascale computing and its convergence with big data analytics has greatly
spurred research interests. The reasons are straightforward. Traditionally, high performance …

The growing use of Big Data frameworks on large machines highlights the importance of
performance issues and the value of High Performance Computing (HPC) technology. This …

Data-intensive applications impact many domains, and their steadily increasing size and
complexity demands highperformance, highly usable environments. We integrate a set of …

Most of the relevant Big Data processing frameworks (eg, Apache Hadoop, Apache Spark)
only support JVM (Java Virtual Machine) languages by default. In order to support non-JVM …

In recent years, the need for the ability to work remotely and subsequently the need for the
availability of remote computer-based systems has increased substantially. This trend has …

Our project is at the interface of Big Data and HPC–High-Performance Big Data computing
and this paper describes a collaboration between 7 collaborating Universities at Arizona …

More and more software libraries and applications in high-performance computing and
distributed systems are coded using the Java programming language. The correctness of …