Results 251 to 260 of about 2,053,524 (303)

On the degree of parallelism for parallel real-time tasks

Journal of Systems Architecture
Qingqiang He, LYU Mingsong, Zhe Jiang
exaly   +3 more sources

Parallelism measures of task graphs for multiprocessors

Microprocessing and Microprogramming, 1994
Many parallel algorithms can be modelled as directed acyclic task graphs. Recently, Degree of Simultaneousness (DS) and Degree of Connection (DC) have been defined as the two measures of parallelism in algorithms represented by task graphs.
V Rajaraman
exaly   +3 more sources

Ada tasking and parallel processors

Proceedings of the conference on Tri-Ada '89 Ada technology in context: application, development, and deployment - TRI-Ada '89, 1989
This paper describes the creation of a shared memory multiprocessor runtime that uses the Ada language tasking model as the basis for CPU allocation. The modifications to an Ada runtime targeted to a single MIL-STD-1750A processor to create a multiprocessor Ada runtime are described. Some performance information is given.
Michael Linnig, Donna Forinash
openaire   +1 more source

Parallel Task Routing for Crowdsourcing

Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 2014
An ideal crowdsourcing or citizen-science system would route tasks to the most appropriate workers, but the best assignment is unclear because workers have varying skill, tasks have varying difficulty, and assigning several workers to a single task may significantly improve output quality.
Jonathan Bragg, Andrey Kolobov, Mausam, Daniel S. Weld   +3 more
openaire   +2 more sources

Streaming Task Parallelism

Proceedings of the 29th ACM on International Conference on Supercomputing, 2015
Stream computing is often associated with regular, data-intensive applications, and more specifically with the family of cyclo-static data-flow models. The term also refers to bulk-synchronous data parallelism on SIMD architectures. Both interpretations are valid but incomplete: streams underline the formal definition of Kahn process networks, a ...
openaire   +3 more sources

FunctionFlow: coordinating parallel tasks

Frontiers of Computer Science, 2018
With the growing popularity of task-based parallel programming, nowadays task-parallel programming libraries and languages are still with limited support for coordinating parallel tasks. Such limitation forces programmers to use additional independent components to coordinate the parallel tasks — the components can be third-party libraries or ...
Xuepeng Fan, Xiaofei Liao, Hai Jin 0001
openaire   +2 more sources

List scheduling of parallel tasks

Information Processing Letters, 1991
The original list scheduling algorithm \textit{R. L. Graham} [Bounds an multprocessing timing anomalies, SIAM J. Appl. Math. 17, 416-429 (1969)] is presented and its performance ratio is shown to be \(\Delta +(m- \Delta)/m\) when parallel tasks are involved.
Quingzhou Wang, Kam-Hoi Cheng
openaire   +1 more source

Elastic Tasks: Unifying Task Parallelism and SPMD Parallelism with an Adaptive Runtime

2015
In this paper, we introduce elastic tasks, a new high-level parallel programming primitive that can be used to unify task parallelism and SPMD parallelism in a common adaptive scheduling framework. Elastic tasks are internally parallel tasks and can run on a single worker or expand to take over multiple workers.
Agrawal, Kunal, Sarkar, Vivek, Sbîrlea, Alina   +2 more
openaire   +2 more sources

Mixed data and task parallelism with HPF and PVM

Cluster Computing, 2000
We present a framework to design efficient and portable HPF applications which exploit a mixture of task and data parallelism. According to the framework proposed, data parallelism is restricted within HPF modules, and task parallelism is achieved by the
Raffaele Perego, Salvatore Orlando
exaly   +1 more source

Extracting task-level parallelism

ACM Transactions on Programming Languages and Systems, 1995
Automatic detection of task-level parallelism (also referred to as functional, DAG, unstructured, or thread parallelism) at various levels of program granularity is becoming increasingly important for parallelizing and back-end compilers.
Milind Girkar, Constantine D. Polychronopoulos   +1 more
openaire   +1 more source