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 …

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 …

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

It is often a challenge to keep input/output tasks/results in order for parallel computations
over data streams, particularly when stateless task operators are replicated to increase …

From the popularization of multi-core architectures, several parallel APIs have emerged,
helping to abstract the programming complexity and increasing productivity in application …

The pipeline is a fundamental pattern to parallelize a series of stage tasks over a sequence
of data in loops. Mainstream pipeline programming frameworks count on data abstractions …

O crescimento e disseminação das arquiteturas paralelas têm conduzido a busca por maior
poder computacional com hardware massivamente paralelo tais como as unidades de …