Results 31 to 40 of about 21,831,698 (267)
SingleCaffe: An Efficient Framework for Deep Learning on a Single Node
IEEE Access, 2018 Deep learning (DL) is currently the most promising approach in complicated applications such as computer vision and natural language processing. It thrives with large neural networks and large datasets.
Chenxu Wang +5 more
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An efficient algorithm for data parallelism based on stochastic optimization
Alexandria Engineering Journal, 2022 Deep neural network models can achieve greater performance in numerous machine learning tasks by raising the depth of the model and the amount of training data samples.
Khalid Abdulaziz Alnowibet +3 more
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Dynamically Changing Parallelism with the Asynchronous Sequential Data Flows
Моделирование и анализ информационных систем, 2020 A statically typed version of the data driven functional parallel computing model is proposed. It enables a representation of dynamically changing parallelism by means of asynchronous serial data flows.
Alexander I. Legalov +3 more
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SpECTRE: A Task-based Discontinuous Galerkin Code for Relativistic Astrophysics [PDF]
, 2017 We introduce a new relativistic astrophysics code, SpECTRE, that combines a discontinuous Galerkin method with a task-based parallelism model. SpECTRE's goal is to achieve more accurate solutions for challenging relativistic astrophysics problems such as
Bohn, Andy +13 more
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Parallelization and Locality Optimization for Red-Black Gauss-Seidel Stencil [PDF]
Jisuanji kexue, 2022 Stencil is a common cyclic nested computing model,which is widely used in many scientific and engineering simulation applications,such as computational electromagnetism,weather simulation,geophysics,ocean simulation and so on.With the deve-lopment of ...
JI Ying-rui, YUAN Liang, ZHANG Yun-quan
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GPU Parallel Method for Deep Learning Image Classification [PDF]
Jisuanji gongcheng, 2023 This paper proposes an improved ring all-reduce algorithm with lower time complexity to improve the low efficiency of multiple Graphics Processing Unit(GPU) parallel transmission in deep-learning image classification scenes.This algorithm optimizes the ...
HAN Yanling, SHEN Siyang, XU Lijun, WANG Jing, ZHANG Yun, ZHOU Ruyan
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A Parallelised ROOT for Future HEP Data Processing [PDF]
EPJ Web of Conferences, 2019 In the coming years, HEP data processing will need to exploit parallelism on present and future hardware resources to sustain the bandwidth requirements. As one of the cornerstones of the HEP software ecosystem, ROOT embraced an ambitious parallelisation
Piparo Danilo +6 more
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Parallelism Analysis of Subroutine-Level Speculative in HPEC [PDF]
Jisuanji gongcheng, 2020 Effective application of Thread-Level Speculation(TLS) technology can improve the hardware resource utilization of multicore chips,and has acquired successful results in automatic parallelization of multiple serial applications.However,it lacks efficient
WANG Xinyi, WANG Yaobin, LI Ling, YANG Yang, BU Deqing, LIU Zhiqin
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Collective Communication Performance Evaluation for Distributed Deep Learning Training
Applied SciencesIn distributed deep learning, the improper use of the collective communication library can lead to a decline in deep learning performance due to increased communication time.
Sookwang Lee, Jaehwan Lee
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Parallel and Distributed Data Management [PDF]
, 2010 Introduction to Topic 5 of Europar ...
Sakellariou, R. +9 more
openaire +4 more sources