Results 11 to 20 of about 3,147,688 (366)
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
International Conference on Parallel Architectures and Compilation Techniques, 2016 Andi Drebes +4 more
semanticscholar +3 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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IEEE Transactions on Parallel and Distributed Systems, 2021 Vast data and computing resources are commonly needed to train deep neural networks, causing an unaffordable price for individual users. Motivated by the increasing demands of deep learning applications, sharing well-trained models becomes popular.
Yunlong Mao +5 more
semanticscholar +1 more source
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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Toward Efficient Similarity Search under Edit Distance on Hybrid Architectures
Information, 2022 Edit distance is the most widely used method to quantify similarity between two strings. We investigate the problem of similarity search under edit distance.
Madiha Khalid +2 more
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Resolving ambiguous polarity stripping ellipsis structures in Persian
Glossa, 2021 Previous studies have shown that English speakers use a range of factors including locality, information structure, and semantic parallelism to interpret clausal ellipsis structures. Yet, the relative importance of each factor is currently underexplored.
Jesse Harris, Vahideh Rasekhi
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