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Automatic Differentiation: Applications, Theory, and Implementations 1

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丛书名： Lecture Notes in Computational Science and engineering

1000年

作者： Martin Bücker George Corliss Uwe Naumann Paul Hovland Boyana Norris

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A Quantum Secret Sharing Scheme Using Orbital Angular Momentum onto Multiple Spin States Based on Fibonacci Compression Encoding

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Communications in Theoretical Physics 2018年第10期70卷 384-390页

作者： Hong Lai Ming-Xing Luo Yong-Jian Xu Josef Pieprzyk Jun Zhang Lei Pan Mehmet A.Orgun School of Computer and Information Science and Centre for Research and Innovation in Software Engineering（RISE） Southwest UniversityChongqing 400715China Information Security and National Computing Grid Laboratory School of Information Science and TechnologySouthwest Jiaotong UniversityChengdu 610031China Data61 Commonwealth Scientific and Industrial Research OrganisationSydneyAustralia Institute of Computer Science Polish Academy of SciencesWarsaw01-248Poland School of Software and Electrical Engineering Swinburne University of TechnologyHawthornVIC3122Australia School of Information Technology Deakin UniversityGeelongVIC3220Australia Department of Computing Macquarie UniversitySydneyNSW 2109Australia Faculty of Information Technology Macao University of Science and TechnologyAvenida Wai LongTaipa999078Macao

Since the use of a quantum channel is very expensive for transmitting large messages, it is vital to develop an effective quantum compression encoding scheme that is easy to implement. Given that, with the single-photon spin-orbit entanglement, we propose a quantum secret sharing scheme using orbital angular momentum onto multiple spin states based on Fibonacci compression encoding. In our proposed scheme, we can represent the frequency of any secret message which is typically collection of bits encodings of text or integers as a bitstring using the base Fibonacci sequence, which is encoded multiple spin states for secret shares transmitted to participants. We demonstrate that Fibonacci compression encoding carries excellent properties that enable us to achieve more robust quantum secret sharing schemes with fewer number of photons.

关键词： spin-orbit entanglement multiple spin states Fibonacci compression encoding quantum secretsharing

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"At scale" author name matching with Hadoop/MapReduce

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Library Hi Tech News 2012年第4期29卷 6-12页

作者： Powell, James Collins, Linn Eberhardt, Ariane Izraelevitz, David Roman, Jorge Dufresne, Thomas Scott, Mark Blake, Miriam Grider, Gary Research Library Los Alamos National Laboratory Los Alamos NM United States International Research and Analysis Group Los Alamos National Laboratory Los Alamos NM United States Risk Analysis and Decision Support Los Alamos National Laboratory Los Alamos NM United States Scientific Software Engineering Los Alamos National Laboratory Los Alamos NM United States High Performance Computing Los Alamos National Laboratory Los Alamos NM United States

Purpose: The purpose of this paper is to describe a process for extracting and matching author names from large collections of bibliographic metadata using the Hadoop implementation of MapReduce. It considers the challenges and risks associated with name matching on such a large-scale and proposes simple matching heuristics for the reduce process. The resulting semantic graphs of authors link names to publications, and include additional features such as phonetic representations of author last names. The authors believe that this achieves an appropriate level of matching at scale, and enables further matching to be performed with graph analysis tools. Design/methodology/approach: A topically-focused collection of metadata records describing peer-reviewed papers was generated based upon a search. The matching records were harvested and stored in the Hadoop Distributed File System (HDFS) for processing by hadoop. A MapReduce job was written to perform coarse-grain author name matching, and multiple papers were matched with authors when the names were very similar or identical. Semantic graphs were generated so that the graphs could be analyzed to perform finer grained matching, for example by using other metadata such as subject headings. Findings: When performing author name matching at scale using MapReduce, the heuristics that determine whether names match should be limited to the rules that yield the most reliable results for matching. Bad rules will result in lots of errors, at scale. MapReduce can also be used to generate or extract other data that might help resolve similar names when stricter rules fail to do so. The authors also found that matching is more reliable within a well-defined topic domain. Originality/value: Libraries have some of the same big data challenges as are found in data-driven science. Big data tools such as hadoop can be used to explore large metadata collections, and these collections can be used as surrogates for other real world, big

关键词： Bibliographies Computer systems Information systems Libraries Metadata Research

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Understanding the use of message passing interface in exascale proxy applications

Understanding the use of message passing interface in exasca...

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作者： Sultana, Nawrin Rüfenacht, Martin Skjellum, Anthony Bangalore, Purushotham Laguna, Ignacio Mohror, Kathryn Department of Computer Science and Software Engineering Auburn University AuburnAL United States Department of Computer Science and Engineering University of Tennessee at Chattanooga ChattanoogaTN United States Department of Computer Science University of Alabama at Birmingham BirminghamAL United States Center for Applied Scientific Computing Lawrence Livermore National Laboratory LivermoreCA United States

The Exascale computing Project (ECP) focuses on the development of future exascale-capable applications. Most ECP applications use the message passing interface (MPI) as their parallel programming model with mini-apps serving as proxies. This paper explores the explicit usage of MPI in such ECP proxy applications. We empirically analyze 14 proxy applications from the ECP Proxy Apps Suite. We use the MPI profiling interface (PMPI) to collect MPI usage patterns in ECP proxy apps. Our analysis shows that a small subset of features from MPI is commonly used in the proxies of exascale-capable applications, even when they reference third-party libraries. This study is intended to provide a better understanding of the use of MPI in current exascale applications. The findings can help focus software investments made for exascale systems in the MPI middleware including optimization, fault-tolerance, tuning, and hardware-offload. © 2020 John Wiley & Sons Ltd

关键词： Message passing

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Logic Programs, Norms and Action 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Alexander Artikis Robert Craven Nihan Kesim Çiçekli Babak Sadighi Kostas Stathis

ISBN: (数字)9783642294143

ISBN: (纸本)9783642294136

This book is dedicated to Marek Sergot, Professor in Computational Logic at Imperial College London, on the occasion of his 60th birthday. Professor Sergot’s scientific contributions range over many different fields. He has developed a series of novel ideas and formal methods bridging areas including artificial intelligence, computational logic, philosophical logic, legal theory, artificial intelligence and law, multi-agent systems and bioinformatics. By combining his background in logic and computing with his interest in the law, deontic logic, action, and related areas, and applying to all his capacity to understand the subtleties of social interaction and normative reasoning, Professor Sergot has opened up new directions of research, and has been a reference, an inspiration, and a model for many researchers in the fields to which he has contributed. The Festschrift includes several reminiscences and introductory essays describing Professor Sergot's achievements, followed by a series of articles on logic programming, temporal reasoning and action languages, artificial intelligence and law, deontic logic and norm-governed systems, and logical approaches to policies.

关键词： Artificial Intelligence Computer Communication Networks Mathematical Logic and Formal Languages software engineering Information Systems Applications (incl. Internet) Logics and Meanings of Programs

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XRL-SHAP-Cache:an explainable reinforcement learning approach for intelligent edge service caching in content delivery networks

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Science China(Information Sciences) 2024年第7期67卷 46-71页

作者： Xiaolong XU Fan WU Muhammad BILAL Xiaoyu XIA Wanchun DOU Lina YAO Weiyi ZHONG School of Software Nanjing University of Information Science and Technology School of Computing and Communications Lancaster University School of Computing Technologies Royal Melbourne Institute of Technology State Key Laboratory for Novel Software Technology Nanjing University School of Computer Science and Engineering University of New South Wales Data 61 Commonwealth Scientific and Industrial Research Organization School of Computer Science Qufu Normal University

Content delivery networks(CDNs) play a pivotal role in the modern internet infrastructure by enabling efficient content delivery across diverse geographical regions. As an essential component of CDNs, the edge caching scheme directly influences the user experience by determining the caching and eviction of content on edge servers. With the emergence of 5G technology, traditional caching schemes have faced challenges in adapting to increasingly complex and dynamic network environments. Consequently, deep reinforcement learning(DRL) offers a promising solution for intelligent zero-touch network governance. However, the blackbox nature of DRL models poses challenges in understanding and making trusting decisions. In this paper,we propose an explainable reinforcement learning(XRL)-based intelligent edge service caching approach,namely XRL-SHAP-Cache, which combines DRL with an explainable artificial intelligence(XAI) technique for cache management in CDNs. Instead of focusing solely on achieving performance gains, this study introduces a novel paradigm for providing interpretable caching strategies, thereby establishing a foundation for future transparent and trustworthy edge caching solutions. Specifically, a multi-level cache scheduling framework for CDNs was formulated theoretically, with the D3QN-based caching scheme serving as the targeted interpretable model. Subsequently, by integrating Deep-SHAP into our framework, the contribution of each state input feature to the agent's Q-value output was calculated, thereby providing valuable insights into the decision-making process. The proposed XRL-SHAP-Cache approach was evaluated through extensive experiments to demonstrate the behavior of the scheduling agent in the face of different environmental *** results demonstrate its strong explainability under various real-life scenarios while maintaining superior performance compared to traditional caching schemes in terms of cache hit ratio, quality of service(QoS),a

关键词： deep reinforcement learning (DRL) explainable artificial intelligence (XAI) multi-level cache content delivery network (CDN) D3QN algorithm Deep-SHAP

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The Quantum Internet (Technical Version)

arXiv

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arXiv 2025年

作者： Rohde, Peter P. Huang, Zixin Ouyang, Yingkai Huang, He-Liang Su, Zu-En Devitt, Simon Ramakrishnan, Rohit Mantri, Atul Tan, Si-Hui Liu, Nana Harrison, Scott Radhakrishnan, Chandrashekar Brennen, Gavin K. Baragiola, Ben Q. Dowling, Jonathan P. Byrnes, Tim Munro, William J. Centre for Quantum Software and Information Faculty of Engineering and Information Technology University of Technology Sydney SydneyNSW Australia Hearne Institute for Theoretical Physics Louisiana State University Baton Rouge United States School of Mathematical and Physical Sciences Macquarie University NSW2109 Australia School of Mathematical and Physical Sciences University of Sheffield SheffieldS3 7RH United Kingdom Henan Key Laboratory of Quantum Information and Cryptography Henan Zhengzhou450000 China Hefei National Laboratory for Physical Sciences at Microscale Department of Modern Physics University of Science & Technology of China Hefei China CAS Centre for Excellence and Synergetic Innovation Centre in Quantum Information & Quantum Physics University of Science & Technology of China Hefei China CAS-Alibaba Quantum Computing Laboratory Shanghai China InstituteQ Aalto University Espoo02150 Finland Indian Institute of Science Bangalore India Singapore University of Technology & Design Singapore Centre for Quantum Technologies National University of Singapore Singapore Horizon Quantum Ireland 24 Fitzwilliam Place Dublin 2 D02 T296 Ireland Institute of Natural Sciences Shanghai Jiao Tong University Shanghai200240 China School of Mathematical Sciences Shanghai Jiao Tong University Shanghai200240 China Ministry of Education Key Laboratory in Scientific and Engineering Computing Shanghai Jiao Tong University Shanghai200240 China Shanghai Artificial Intelligence Laboratory Shanghai China University of Michigan Shanghai Jiao Tong University Joint Institute Shanghai200240 China Leibniz Institute for Research & Information in Education Frankfurt am Main Germany Department of Computer Science and Engineering NYU Shanghai 567 West Yangsi Road Shanghai200124 China Centre of Excellence in Engineered Quantum Systems Macquarie University NSW Australia Centre for Quantum Computation and Communication Technology School of Science RMIT University VIC

The desire to share and unite remote digital assets motivated the development of the classical internet, the enabler of the entire 21st century economy and our modern way of life. As we enter the quantum era, it is to be expected there will be a similar demand for networking quantum assets, motivating a global quantum internet for bringing together the world's quantum resources, leveraging off their exponential trajectory in capability. We present models for quantum networking, how they might be applied in the future, and the implications they will have. Socially, economically, politically and geostrategically, the upcoming era of quantum supremacy will be as significant for the 21st century as the transistor was for the 20th. The inherently different scaling in the computational power of quantum computers fundamentally changes the dynamics of how they will operate in the future. Given their high expected initial cost, a client/server model for outsourcing computation will be essential for enabling the accessibility and proliferation of this technology, and ensuring its economic viability. We therefore anticipate the emergence of cloud quantum computing, a model for outsourcing quantum computations to the network. We argue that economic efficiency will mandate that all future quantum computers be united into a single global virtual quantum computer, offering exponentially more power to all network participants than if they were to keep their resources to themselves. This model for the allocation of computational resources is uniquely quantum, with no classical analogue, completely altering the economic landscape for the future of computation. Given the sensitivity of much of the data to which future quantum computers are going to foreseeably be applied, protocols for encrypted quantum computation will be essential - the outsourcing of computations that neither an eavesdropper nor even the server performing the computation can spy upon. This will enable new models fo

关键词： Outsourcing

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A fully implicit method for lattice boltzmann equations

A fully implicit method for lattice boltzmann equations

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作者： Huang, Jizu Yang, Chao Cai, Xiao-Chuan Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Institute of Software Chinese Academy of Sciences Beijing100190 China State Key Laboratory of Computer Science Beijing100190 China Department of Computer Science University of Colorado Boulder BoulderCO80309 United States

Existing approaches for solving the lattice Boltzmann equations with finite difference methods are explicit and semi-implicit;both have certain stability constraints on the time step size. In this work, a fully implicit second-order finite difference scheme is developed. We focus on a parallel, highly scalable, Newton-Krylov-RAS algorithm for the solution of a large sparse nonlinear system of equations arising at each time step. Here, RAS is a restricted additive Schwarz preconditioner based on a first-order spatial discretization. We show numerically that by using the fully implicit method the time step size is no longer constrained by the CFL condition, and the Newton-Krylov- RAS algorithm is scalable on a supercomputer with more than ten thousand processors. Moreover, to calculate the steady state solution we investigate an adaptive time stepping strategy. The total compute time required by the implicit method with adaptive time stepping is much smaller than that of an explicit method for several test cases. © 2015 Society for Industrial and Applied Mathematics.

关键词： Finite difference method

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Visual sentiment analysis for brand monitoring enhancement

Visual sentiment analysis for brand monitoring enhancement

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International Symposium on Image and Signal Processing and Analysis

作者： Theodoros Giannakopoulos Michalis Papakostas Stavros Perantonis Vangelis Karkaletsis Computational Intelligence Lab National Center for Scientific Research DEMOKRITOS Athens Greece Heracleia Human Centered Computing Laboratory University of Texas Arlington USA Software and Knowledge Engineering Lab National Center for Scientific Research DEMOKRITOS Athens Greece

Brand monitoring and reputation management are vital tasks in all modern business intelligence frameworks. However, recent related technologies rely mostly on the textual aspect of online content, in order to extract the underlying sentiment with respect to particular brands. In this work, we demonstrate the sentiment analysis method in the context of a brand monitoring framework, breaking the text-only barrier in the field. Towards this end, a wide range of visual features is extracted, some of which focus on the underlying semiotics and aesthetics of the images. In addition, we employ textual information embedded in the images under study, by adopting text mining techniques that focus on extracting sentiment. We evaluate the classification task for the particular binary task (negative vs positive sentiment) and propose a fusion approach that combines the two different modalities. Finally, the evaluation procedure has been carried out in the context of two different use cases, namely: (a) a general image sentiment classifier for brand and advertising images and (b) a brand-specific classification procedure, according to which the brand of the input images is known a-priori. Results have proven that the visual-based sentiment classification of brand and advertising information can outperform the respective text-based classification. In addition, fusing the two modalities leads to significant performance boosting.

关键词： Visualization Apertures Image edge detection Random access memory Ferroelectric films Nonvolatile memory

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Optimizing Cloud computing Resource Usage for Hemodynamic Simulation

Optimizing Cloud Computing Resource Usage for Hemodynamic Si...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： William Ladd Christopher Jensen Madhurima Vardhan Jeff Ames Jeff R. Hammond Erik W. Draeger Amanda Randles Biomedical Engineering Duke University Durham NC USA HPC Software NVIDIA Helsinki Oy Helsinki Finland Center for Applied Scientific Computing Lawrence Livermore National Laboratory Livermore CA USA

Cloud computing resources are becoming an increasingly attractive option for simulation workflows but require users to assess a wider variety of hardware options and associated costs than required by traditional in-house hardware or fixed allocations at leadership computing facilities. The pay-as-you-go model used by cloud providers gives users the opportunity to make more nuanced cost-benefit decisions at runtime by choosing hardware that best matches a given workload, but creates the risk of suboptimal allocation strategies or inadvertent cost overruns. In this work, we propose the use of an iteratively-refined performance model to optimize cloud simulation campaigns against overall cost, throughput, or maximum time to solution. Hemodynamic simulations represent an excellent use case for these assessments, as the relative costs and dominant terms in the performance model can vary widely with hardware, numerical parameters and physics models. Performance and scaling behavior of hemodynamic simulations on multiple cloud services as well as a traditional compute cluster are collected and evaluated, and an initial performance model is proposed along with a strategy for dynamically refining it with additional experimental data.

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