A recurrent challenge in real‐world applications is autonomous management of the
executions at run‐time. In this vein, stream processing is a class of applications that compute …

Multi-core systems are any computing device nowadays and stream processing applications
are becoming recurrent workloads, demanding parallelism to achieve the desired quality of …

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

In a fast-changing data-driven world, real-time data processing systems are becoming
ubiquitous in everyday applications. The increasing data we produce, such as audio, video …

Stream processing applications are common computing workloads that demand parallelism
to increase their performance. As in the past, parallel programming remains a difficult task …

Abstract The NAS Parallel Benchmarks (NPB), originally implemented mostly in Fortran, is a
consolidated suite containing several benchmarks extracted from Computational Fluid …

Benchmarking is a way to study the performance of new architectures and parallel
programming frameworks. Well-established benchmark suites such as the NAS Parallel …

Health data science systems are becoming key for supporting healthcare decision-making
processes. However, these systems should achieve continuous data processing and adapt …

Parallel programming has been a challenging task for application programmers. Stream
processing is an application domain present in several scientific, enterprise, and financial …

Stream processing applications deal with millions of data items continuously generated over
time. Often, they must be processed in real-time and scale performance, which requires the …