Big data has revolutionized science and technology leading to the transformation of our
societies. High-performance computing (HPC) provides the necessary computational power …

Task-based programming models like OmpSs-2 and OpenMP provide a flexible data-flow
execution model to exploit dynamic, irregular and nested parallelism. Providing an efficient …

Recent work has shown that building GPUs with hundreds of SMs in a single monolithic chip
will not be practical due to slowing growth in transistor density, low chip yields, and …

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

Data-flow programming models have become a popular choice for writing parallel
applications as an alternative to traditional work-sharing parallelism. They are better suited …

Due to the challenges in providing adequate memory access to many cores on a single
processor, Multi-Die and Multi-Socket based multicore systems are becoming mainstream …

The sequential task flow (STF) model introduces implicit data dependences to exploit task-
based parallelism, simplifying programming but also introducing non-negligible runtime …

Compared to threads, tasks are a more fine-grained alternative. The task parallel
programming model offers benefits in terms of better performance portability and better load …

Field programmable gate arrays (FPGAs) are fundamentally different to fixed processors
architectures because their memory hierarchies can be tailored to the needs of an algorithm …

OpenMP tasking supports parallelization of irregular algorithms. Recent OpenMP
specifications extended tasking to increase functionality and to support optimizations, for …