Current parallel programming frameworks aid developers to a great extent in implementing
applications that exploit parallel hardware resources. Nevertheless, developers require …

OpenMP is an industry and academic standard for parallel programming. However, using it
for developing parallel stream processing applications is complex and challenging. OpenMP …

Data generation, collection, and processing is an important workload of modern computer
architectures. Stream or high-intensity data flow applications are commonly employed in …

Current high-performance computer systems used for scientific computing typically combine
shared memory computational nodes in a distributed memory environment. Extracting high …

This paper presents the design, development, and implementation of Kulla, a virtual
container-centric construction model that mixes loosely coupled structures with a parallel …

The execution of complex distributed applications in exascale systems faces many
challenges, as it involves empirical evaluation of countless code variations and application …

Modern supercomputer architectures have grown increasingly complex and diverse since
the end of Moore's law in the mid-2000s, and are far more difficult to program than their …

In the world of Big Data analytics, there is a series of tools aiming at simplifying
programming applications to be executed on clusters. Although each tool claims to provide …

We discuss the extended parallel pattern set identified within the EU-funded project
RePhrase as a candidate pattern set to support data intensive applications targeting …

This work studies the issues related to dynamic memory management in Data Stream
Processing, an emerging paradigm enabling the real-time processing of live data streams. In …