Results 71 to 80 of about 21,055,470 (353)

Data Parallelism in Java

, 1998
Java supports threads and remote method invocation, but it does not support either data-parallel or distributed programming. This paper discusses Java’s shortcomings with respect to data-parallel programming and presents workarounds. The technical contributions of this paper are twofold: a source-to-source transformation that maps foral l statements ...
openaire   +3 more sources

Superior Electromechanical Power at Rare‐Earth Manipulated Glassy Morphotropic Phase Transitions

Advanced Science, EarlyView.
An effective physical approach named Rare‐earth Manipulated Glassy Morphotropic Phase Transitions has been experimentally developed and theoretically validated to achieve significant enhancements of 135% and 50% in electrostrain and elastic modulus of lead‐free ferroelectrics respectively, further enabling the significant boost of requisite driving ...
Le Zhang, Liqiang He, Shuyuan Xu, Haoyu Wang, Yunlong Sun, Yating Ran, Dong Wang, Kaiyun Chen, Junkai Deng, Zibin Chen, Danyang Wang, Michael A. Carpenter, Sen Yang   +12 more
wiley   +1 more source

User privacy prevention model using supervised federated learning‐based block chain approach for internet of Medical Things

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract This research focuses on addressing the privacy issues in healthcare advancement monitoring with the rapid establishment of the decentralised communication system in the Internet of Medical Things (IoMT). An integrated blockchain homomorphic encryption standard with an in‐build supervised learning‐based smart contract is designed to improvise ...
Chandramohan Dhasarathan, Mohammad Kamrul Hasan, Shayla Islam, Salwani Abdullah, Shailesh Khapre, Dalbir Singh, Abdulaziz A. Alsulami, Ali Alqahtani   +7 more
wiley   +1 more source

Strategies and Principles of Distributed Machine Learning on Big Data

Engineering, 2016
The rise of big data has led to new demands for machine learning (ML) systems to learn complex models, with millions to billions of parameters, that promise adequate capacity to digest massive datasets and offer powerful predictive analytics (such as ...
Eric P. Xing, Qirong Ho, Pengtao Xie, Dai Wei   +3 more
doaj   +1 more source

Weakly Supervised Learning with Multi-Stream CNN-LSTM-HMMs to Discover Sequential Parallelism in Sign Language Videos

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
In this work we present a new approach to the field of weakly supervised learning in the video domain. Our method is relevant to sequence learning problems which can be split up into sub-problems that occur in parallel.
Oscar Koller, N. C. Camgoz, H. Ney, R. Bowden   +3 more
semanticscholar   +1 more source

Reconstructing Three‐Dimensional Optical Anisotropy with Tomographic Müller‐Polarimetric Microscopy

Advanced Science, EarlyView.
Tomographic Müller polarimetric microscopy is a novel imaging technique that resolves 3D birefringent properties of bulky samples, unveiling hierarchical nanostructures at microscopic resolution. Based on incoherent visible‐light polarimetry, it achieves experimental simplicity by eliminating phase measurements.
Yang Chen, Arthur Baroni, Torne Tänzer, Leonard Nielsen, Marianne Liebi   +4 more
wiley   +1 more source

OpenCL Actors - Adding Data Parallelism to Actor-based Programming with CAF

, 2017
The actor model of computation has been designed for a seamless support of concurrency and distribution. However, it remains unspecific about data parallel program flows, while available processing power of modern many core hardware such as graphics ...
A Klöckner, D Charousset, G Agha, G Agha, J Nickolls, JD Owens, K Wu, L Dagum, S Srinivasan, S Wienke, T Desell   +10 more
core   +1 more source

Blockchain‐Empowered H‐CPS Architecture for Smart Agriculture

Advanced Science, EarlyView.
This article reviews the current system architectures for smart agriculture and proposes a blockchain‐empowered hierarchical cyber‐physical system (H‐CPS) framework. It discusses the challenges and outlines future research directions, including the use of semantic blockchain to handle complex data and models.
Xiaoding Wang, Qibin Wu, Haitao Zeng, Xu Yang, Hui Cui, Xun Yi, Md. Jalil Piran, Ming Luo, Youxiong Que   +8 more
wiley   +1 more source

An integration of autonomic computing with multicore systems for performance optimization in Industrial Internet of Things

IET Communications, EarlyView., 2022
Abstract The goal of this work is to investigate how the self‐awareness characteristic of autonomic computing, paired with existing performance optimization rules, may be used in applications to minimise multi‐core processor performance concerns. The suggested self‐awareness technique can assist applications in self‐execution while also assisting other
Surendra Kumar Shukla, Bhaskar Pant, Wattana Viriyasitavat, Devvret Verma, Sandeep Kautish, Gaurav Dhiman, Amandeep Kaur, Kannan Srihari, Sachi Nandan Mohanty   +8 more
wiley   +1 more source

Pipeline Parallelism With Elastic Averaging

IEEE Access
To accelerate the training speed of massive DNN models on large-scale datasets, distributed training techniques, including data parallelism and model parallelism, have been extensively studied.
Bongwon Jang, In-Chul Yoo, Dongsuk Yook
doaj   +1 more source