Results 11 to 20 of about 3,076,045 (348)
Task parallelism and high-performance languages [PDF]
IEEE Parallel & Distributed Technology: Systems & Applications, 1996 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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The Eureka Programming Model for Speculative Task Parallelism [PDF]
European Conference on Object-Oriented Programming, 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.
S. Imam, Vivek Sarkar
semanticscholar +4 more sources
Integrating task and data parallelism [PDF]
Proceedings of the 1993 ACM/IEEE conference on Supercomputing - Supercomputing '93, 1993 Many models of concurrency and concurrent programming have been proposed; most can be categorized as either task-parallel (based on functional decomposition) or data-parallel (based on data decomposition). Task-parallel models are most effective for expressing irregular computations; data-parallel models are most effective for expressing regular ...
Ian Foster, Carl Kesselman
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Scalable Task Parallelism for NUMA
International Conference on Parallel Architectures and Compilation Techniques, 2016 Andi Drebes +4 more
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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
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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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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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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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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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