Results 51 to 60 of about 364,302 (257)
Timing Analysis for DAG-based and GFP Scheduled Tasks [PDF]
, 2014 Modern embedded systems have made the transition from single-core to multi-core architectures, providing performance improvement via parallelism rather than higher clock frequencies. DAGs are considered among the most generic task models in the real-time
Marinho, José, Petters, Stefan M.
core
Tackling Exascale Software Challenges in Molecular Dynamics Simulations with GROMACS
, 2015 GROMACS is a widely used package for biomolecular simulation, and over the last two decades it has evolved from small-scale efficiency to advanced heterogeneous acceleration and multi-level parallelism targeting some of the largest supercomputers in the ...
A Arnold +21 more
core +1 more source
The Eureka Programming Model for Speculative Task Parallelism [PDF]
, 2015 In this paper, we describe the Eureka Programming Model (EuPM) that simplifies the expression of speculative parallel tasks, and is especially well suited for parallel search and optimization applications.
Imam, Shams, Sarkar, Vivek
core +2 more sources
Executing linear algebra kernels in heterogeneous distributed infrastructures with PyCOMPSs
Oil & Gas Science and Technology, 2018 Python is a popular programming language due to the simplicity of its syntax, while still achieving a good performance even being an interpreted language. The adoption from multiple scientific communities has evolved in the emergence of a large number of
Amela Ramon +4 more
doaj +1 more source
Parallelism Strategies for Big Data Delayed Transfer Entropy Evaluation
Algorithms, 2019 Generated and collected data have been rising with the popularization of technologies such as Internet of Things, social media, and smartphone, leading big data term creation. One class of big data hidden information is causality.
Jonas R. Dourado +2 more
doaj +1 more source
Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences [PDF]
arXiv, 2022 Parallelizing Gated Recurrent Unit (GRU) networks is a challenging task, as the training procedure of GRU is inherently sequential. Prior efforts to parallelize GRU have largely focused on conventional parallelization strategies such as data-parallel and model-parallel training algorithms.
arxiv
A Pipeline-Based ODE Solving Framework
IEEE AccessThe traditional parallel solving methods of ordinary differential equations (ODE) are mainly classified into task-parallelism, data-parallelism, and instruction-level parallelism.
Ruixia Cao, Shangjun Hou, Lin Ma
doaj +1 more source
Mapping the Join Calculus to Heterogeneous Hardware [PDF]
Electronic Proceedings in Theoretical Computer Science, 2013 As modern architectures introduce additional heterogeneity and parallelism, we look for ways to deal with this that do not involve specialising software to every platform.
Peter Calvert, Alan Mycroft
doaj +1 more source
Alleviating the software parallelization task
, 2021 Despite decades of research into parallelizing compiler technology, software parallelization remains a largely manual task, which is complex, time-consuming, and error-prone. An embarrassingly parallel problem can be hidden behind a serial algorithm, thoughtless software design, or unsuccessfully chosen lower-level constructs, such as data structures ...
openaire +2 more sources
Scheduling parallel tasks on hypercubes [PDF]
Electronics Letters, 1994 The authors consider the problem of non-pre-emptively scheduled independent parallel tasks with communication overhead on a d-dimensional hypercube system. To find a schedule such that the schedule length is minimised is NP-hard. Therefore, a simple heuristic algorithm is investigated and its performance boundary is derived as (2+In m-1/m), where m=2 ...
Lin, J.-F., Chen, S.-J.
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