Results 61 to 70 of about 178,091 (333)
Efficient electro-magnetic analysis of a GPU bitsliced AES implementation
Cybersecurity, 2020 The advent of CUDA-enabled GPU makes it possible to provide cloud applications with high-performance data security services. Unfortunately, recent studies have shown that GPU-based applications are also susceptible to side-channel attacks.
Yiwen Gao, Yongbin Zhou, Wei Cheng
doaj +1 more source
Symmetries in data parallelism [PDF]
The Computer Journal, 1995 A comprehensive formalization of data-parallel (DP) symmetries in an imperative language paradigm without nesting is presented, which includes translational, affine and access symmetries. A subtyping system which takes these symmetries into account is discussed.
openaire +2 more sources
Perovskite Microwires for Room Temperature Exciton‐Polariton Neural Network
Advanced Materials, EarlyView.Exciton‐polaritons are explored as a novel platform for optical neuromorphic computing at room temperature using a monocrystalline perovskite waveguide. Demonstrating non‐equilibrium Bose‐Einstein condensation, this work achieves machine learning tasks such as classification and object detection, marking a key advance toward energy‐efficient, practical
Andrzej Opala +9 more
wiley +1 more source
The VolumePro Volume Rendering Cluster: A Vital Component of Parallel End-to-End Solution [PDF]
, 2003 As data sets, both acquired from scanners and those generated from complex simulations, grow in size and complexity, researchers continue to push the boundaries of the amount of data that can be viewed, processed and analyzed interactively.
Lombeyda, Santiago, McCorquodale, John
core
Applied SciencesDemonstrating parallelism in quantitative laboratory tests is crucial to ensure accurate reporting of data and minimise risks to patients. Regulatory authorities make the demonstration of parallelism before clinical use approval mandate.
Axel Petzold
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, 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
Coupling Enhanced Diffractive Deep Neural Network with Structural Nonlinearity
Advanced Photonics Research, EarlyView.Here, structural nonlinearity is introduced into diffractive deep neural networks (D2NNs) by incorporating encoding‐free data repetition layers, enabling high‐order optical nonlinearity while reducing the system complexity. Additionally, to enhance the design accuracy of D2NNs, a graph neural network is developed to characterize the coupling effects ...
Ouling Wu +5 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 +3 more
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Ultralow Loss Coupling Tuning of Photonic Accelerators
Advanced Photonics Research, EarlyView.A polymer material cured by electron beam is used to perform precise and ultralow loss tuning on photonic accelerators made for highly efficient computation. The versatility of the technique is demonstrated on a large number of directional coupler devices with varying initial coupling ratios and application on a crossbar array for matrix multiplication
Zhongyu Tang +5 more
wiley +1 more source
BISMO: A Scalable Bit-Serial Matrix Multiplication Overlay for Reconfigurable Computing
, 2018 Matrix-matrix multiplication is a key computational kernel for numerous applications in science and engineering, with ample parallelism and data locality that lends itself well to high-performance implementations.
Rasnayake, Lahiru +2 more
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