ListarGrupos de investigación por tema "Hybrid parallelism"
Mostrando ítems 1-4 de 4
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A general and efficient divide-and-conquer algorithm framework for multi-core clusters
(SpringerLink, 2017)[Abstract]Divide-and-conquer is one of the most important patterns of parallelism, being applicable to a large variety of problems. In addition, the most powerful parallel systems available nowadays are computer clusters ... -
A Highly Optimized Skeleton for Unbalanced and Deep Divide-And-Conquer Algorithms on Multi-Core Clusters
(Springer, 2022)[Abstract] Efficiently implementing the divide-and-conquer pattern of parallelism in distributed memory systems is very relevant, given its ubiquity, and difficult, given its recursive nature and the need to exchange tasks ... -
High-performance dataflow computing in hybrid memory systems with UPC++ DepSpawn
(Springer, 2021)[Abstract]: Dataflow computing is a very attractive paradigm for high-performance computing, given its ability to trigger computations as soon as their inputs are available. UPC++ DepSpawn is a novel task-based library ... -
The New UPC++ DepSpawn High Performance Library for Data-Flow Computing with Hybrid Parallelism
(Springer, 2022)[Abstract] Data-flow computing is a natural and convenient paradigm for expressing parallelism. This is particularly true for tools that automatically extract the data dependencies among the tasks while allowing to exploit ...