Results 1 to 10 of about 27,095 (213)
Fiber Clustering Acceleration With a Modified Kmeans++ Algorithm Using Data Parallelism [PDF]
Frontiers in Neuroinformatics, 2021 Fiber clustering methods are typically used in brain research to study the organization of white matter bundles from large diffusion MRI tractography datasets.
Isaac Goicovich +8 more
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Relating data-parallelism and (and-) parallelism in logic programs [PDF]
Computer Languages, 1995 Much work has been done in the áreas of and-parallelism and data parallelism in Logic Programs. Such work has proceeded to a certain extent in an independent fashion. Both types of parallelism offer advantages and disadvantages. Traditional (and-) parallel models offer generality, being able to exploit parallelism in a large class of programs ...
Hermenegildo, Manuel V. +1 more
core +4 more sources
Accelerating Distributed SGD With Group Hybrid Parallelism
IEEE Access, 2021 The scale of model parameters and datasets is rapidly growing for high accuracy in various areas. To train a large-scale deep neural network (DNN) model, a huge amount of computation and memory is required; therefore, a parallelization technique for ...
Kyung-No Joo, Chan-Hyun Youn
doaj +1 more source
Applied Sciences, 2021 The recent unprecedented success of deep learning (DL) in various fields is underlied by its use of large-scale data and models. Training a large-scale deep neural network (DNN) model with large-scale data, however, is time-consuming.
Yunyong Ko, Sang-Wook Kim
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Communication Optimization Schemes for Accelerating Distributed Deep Learning Systems
Applied Sciences, 2020 In a distributed deep learning system, a parameter server and workers must communicate to exchange gradients and parameters, and the communication cost increases as the number of workers increases.
Jaehwan Lee +4 more
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Collision Detection Based on Data Parallelism [PDF]
Jisuanji gongcheng, 2017 The application of accurate collision detection in Building Information Modeling(BIM) is facing the increasingly large amount of data,but the serial execution cannot continue to accelerate with the increasing frequency of the processor.Aiming at this ...
PENG Zhen,WU Baifeng
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IEEE Access, 2023 Deep learning (DL) has gained increasing prominence in latency-critical artificial intelligence (AI) applications. Due to the intensive computational requirements of these applications, cloud-centric approaches have been attempted to address this issue ...
Emre Kilcioglu +2 more
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Algebraic data parallelism implementation in HPF
Lietuvos Matematikos Rinkinys, 2002 There is not abstract.
Valdona Judickaitė +2 more
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Achieving new SQL query performance levels through parallel execution in SQL Server [PDF]
E3S Web of Conferences, 2023 This article provides an in-depth look at implementing parallel SQL query processing using the Microsoft SQL Server database management system. It examines how parallelism can significantly accelerate query execution by leveraging multi-core processors ...
Nuriev Marat +3 more
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Parallelizing the Data Cube [PDF]
, 2001 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Frank K. H. A. Dehne +3 more
openaire +2 more sources