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torcpy: Supporting task parallelism in Python
SoftwareX, 2020 Task-based parallelism has been established as one of the main forms of code parallelization, where asynchronous tasks are launched and distributed across the processing units of a local machine, a cluster or a supercomputer.
P.E. Hadjidoukas +5 more
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Adaptive memory reservation strategy for heavy workloads in the Spark environment [PDF]
PeerJ Computer ScienceThe rise of the Internet of Things (IoT) and Industry 2.0 has spurred a growing need for extensive data computing, and Spark emerged as a promising Big Data platform, attributed to its distributed in-memory computing capabilities.
Bohan Li +6 more
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Extracting task-level parallelism [PDF]
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 +1 more
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Multi-Satellite Task Parallelism via Priority-Aware Decomposition and Dynamic Resource Mapping
MathematicsMulti-satellite collaborative computing has achieved task decomposition and collaborative execution through inter-satellite links (ISLs), which has significantly improved the efficiency of task execution and system responsiveness.
Shangpeng Wang +4 more
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Adaptive Parallelism for OpenMP Task Parallel Programs [PDF]
, 2000 We present a system that allows task parallel OpenMP programs to execute on a network of workstations (NOW) with a variable number of nodes. Such adaptivity, generally called adaptive parallelism, is important in a multi-user NOW environment, enabling the system to expand the computation onto idle nodes or withdraw from otherwise occupied nodes.
Alex Scherer +3 more
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Task parallelism and high-performance languages [PDF]
IEEE Parallel & Distributed Technology: Systems & Applications, 1994 The definition of High Performance Fortran (HPF) is a significant event in the maturation of parallel computing: it represents the first parallel language that has gained widespread support from vendors and users. The subject of this paper is to incorporate support for task parallelism.
Ian Foster
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Integrating task and data parallelism [PDF]
Proceedings of the 1993 ACM/IEEE conference on Supercomputing - Supercomputing '93, 1993 The increased computational power of massively parallel computers and high bandwidth low latency computer networks will make a wide range of previously unpractical problems feasible. This will inevitably result in the need to develop parallel software whose complexity far exceeds that of parallel programs being developed today.
Foster, Ian, Kesselman, Carl
+7 more sources
Jet: Fast quantum circuit simulations with parallel task-based tensor-network contraction [PDF]
Quantum, 2022 We introduce a new open-source software library $Jet$, which uses task-based parallelism to obtain speed-ups in classical tensor-network simulations of quantum circuits.
Trevor Vincent +6 more
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Applied Sciences, 2021 The rapid development of artificial intelligence technology has made deep neural networks (DNNs) widely used in various fields. DNNs have been continuously growing in order to improve the accuracy and quality of the models.
Yingchi Mao +4 more
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Characterizing task-based OpenMP programs. [PDF]
PLoS ONE, 2015 Programmers struggle to understand performance of task-based OpenMP programs since profiling tools only report thread-based performance. Performance tuning also requires task-based performance in order to balance per-task memory hierarchy utilization ...
Ananya Muddukrishna +2 more
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