Results 1 to 10 of about 11,763 (158)
Applied Sciences (Switzerland), 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, Zijian Tu, Qingyong Wang
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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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Exploiting Task Parallelism with OpenCL: A Case Study
Journal of Signal Processing Systems, 2018 While data parallelism aspects of OpenCL have been of primary interest due to the massively data parallel GPUs being on focus, OpenCL also provides powerful capabilities to describe task parallelism.
Pekka Jääskeläinen +2 more
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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
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Exploiting nested task-parallelism in the H -LU factorization [PDF]
Journal of Computational Science, 2019 We address the parallelization of the LU factorization of hierarchical matrices (-matrices) arising from boundary element methods. Our approach exploits task-parallelism via the OmpSs programming model and runtime, which discovers the data-flow ...
Rocio Carratalá-Sáez +2 more
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Exploiting Vector and Multicore Parallelism for Recursive, Data- and Task-Parallel Programs
ACM SIGPLAN Notices, 2017 Modern hardware contains parallel execution resources that are well-suited for data-parallelism vector units and task parallelism multicores. However, most work on parallel scheduling focuses on one type of hardware or the other. In this work, we present
Sriram Krishnamoorthy, Kulkarnimilind
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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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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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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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