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About 10,000 papers for “Distributed computing”

Distributed Computing Group

David Hasenfratz, Prof Dr, Roger Wattenhofer et al. · 2014

Practically any notebook or desktop computer today is equipped with dual-core chips and already quad-core chips are coming to the market. In contrast a huge junk of the available software today is not able to make full use out of these mighty processors. With monitors, semaphores or locks it is hard and time-consuming to write efficient and correct code which scales well with the number of increasing cores. Transactional Memory aims to solve this problem. The idea of Transactional Memory (TM) has been brought from database sys-tems to programming. TM is a hot research topic nowadays, considered by many researchers to be one of the most promising solutions for concurrency control. In a TM system, the contention manager is responsible for resolving the con-flicts between transactions. There are already a number of policies available, how-ever benchmarks have been limited and neither theory, nor the benchmarks consid-ered, yield a clear picture of how a contention manager should make its decision. None of the policies is outperforming all the others on the tested benchmarks. This thesis introduces 10 new contention manager policies. Two of them, the AccurateTimestampBackoffTime and TransactionalArrayReactivateAny man-agers, show very good results. Both outperform all the published managers on three of the tested benchmarks. On the other two benchmarks the TransactionalAr-rayReactivateAny manager performs equally well as the best published policy. On one benchmark the AccurateTimestampBackoffTime policy is worse than the best published manager. The benchmarks were executed on 4 AMD Quadcore Opteron 8350 (2.0 GHz) processors, using the DSTM2.1 Java library from Herlihy et al. Acknowledgment I would like to thank Prof. Dr. Roger Wattenhofer for giving me the opportunity to write my semester thesis at the Distributed Computing Group. Special thanks go to Johannes Schneider who supervised my work very com-petently. Thank you for having an open ear for all my problems and questions at any time during the day. i ii

Cited by 0

Unclogging distributed computing

David E. Hartman · IEEE Spectrum · 1992

The need for an efficient, flexible, secure, yet cost-effective multivendor distributed computing environment is discussed. A comprehensive effort toward this goal, the Distributed Computing Environment (DCE) software, is described. Developed by an industry-supported R&D organization with more than 330 members worldwide, the DCE focuses on four problems that require technical solutions: the diversity of operating environments, the (generally large) number of interconnected computers, the need to maintain security, and the need to provide opportunities both for growth and for new network applications.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cited by 15

Deploying Distributed Computing

Steve Sawyer, William Gibbons · IGI Global eBooks · 2011

This teaching case describes the efforts of one department in a large organization to migrate from an internally developed, mainframe-based, computing system to a system based on purchased software running on a client/server architecture. The case highlights issues with large scale software implementations such as those demanded by enterprise resource package (ERP) installations. Often, the ERP selected by an organization does not have all the required functionality. This demands purchasing and installing additional packages (known colloquially as “bolt-ons”) to provide the needed functionality. These implementations lead to issues regarding oversight of the technical architecture, both project and technology governance, and user department capability for managing the installation of new systems. Request access from your librarian to read this chapter's full text.

Cited by 0

Distributed computing column

Cynthia Dwork · ACM SIGACT News · 1989

article Free Access Share on Distributed computing column Author: C. Dwork IBM Almaden Research Center, K53/802 650 Harry Road, San Jose, CA. IBM Almaden Research Center, K53/802 650 Harry Road, San Jose, CA.View Profile Authors Info & Claims ACM SIGACT NewsVolume 20Issue 4Nov. 1989 pp 14–16https://doi.org/10.1145/74074.74076Published:01 November 1989Publication History 0citation87DownloadsMetricsTotal Citations0Total Downloads87Last 12 Months10Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

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Tessellated Distributed Computing

Ali Khalesi, Petros Elia · IEEE Transactions on Information Theory · 2025

The work considers the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i>-server distributed computing scenario with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i> users requesting functions that are linearly-decomposable over an arbitrary basis of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> real (potentially non-linear) subfunctions. In our problem, the aim is for each user to receive their function outputs, allowing for reduced reconstruction error (distortion) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\epsilon $ </tex-math></inline-formula>, reduced computing cost (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\gamma $ </tex-math></inline-formula>; the fraction of subfunctions each server must compute), and reduced communication cost (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\delta $ </tex-math></inline-formula>; the fraction of users each server must connect to). For any given set of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i> requested functions — which is here represented by a coefficient matrix <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathbf {F} \in \mathbb {R}^{K \times L}$ </tex-math></inline-formula> — our problem is made equivalent to the open problem of sparse matrix factorization that seeks — for a given parameter <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</i>, representing the number of shots for each server — to minimize the reconstruction distortion <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\frac {1}{KL}\|\mathbf {F} - \mathbf {D}\mathbf {E}\|^{2}_{F}$ </tex-math></inline-formula> over all <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\delta $ </tex-math></inline-formula>-sparse and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\gamma $ </tex-math></inline-formula>-sparse matrices <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathbf {D}\in \mathbb {R}^{K \times NT}$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathbf {E} \in \mathbb {R}^{NT \times L}$ </tex-math></inline-formula>. With these matrices respectively defining which servers compute each subfunction, and which users connect to each server, we here design our <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathbf {D},\mathbf {E}$ </tex-math></inline-formula> by designing tessellated-based and SVD-based fixed support matrix factorization methods that first split F into properly sized and carefully positioned submatrices, which we then approximate and then decompose into properly designed submatrices of D and E. For the zero-error case and under basic dimensionality assumptions, the work reveals achievable computation-vs-communication corner points <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$(\gamma ,\delta)$ </tex-math></inline-formula> which, for various cases, are proven optimal over a large class of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathbf {D},\mathbf {E}$ </tex-math></inline-formula> by means of a novel tessellations-based converse. Subsequently, for large <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i>, and under basic statistical assumptions on F, the average achievable error <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\epsilon $ </tex-math></inline-formula> is concisely expressed using the incomplete first moment of the standard Marchenko-Pastur distribution, where this performance is shown to be optimal over a large class of D and E. In the end, the work also reveals that the overall achieved gains over baseline methods are unbounded.

Cited by 0

in Distributed Computing

Salman Zubair Toor, C Salman Zubair Toor · 2010

This thesis covers three areas in the field of enabling distributed computing infrastructure for scientific applications. In the first paper we present tools for general purpose solutions using portal technology while the second paper addresses the access of grid resources within an application problem solving environment for a specific domain. • E. Elmroth, S. Holmgren, J. Lindemann, S. Toor, and P–O. Östberg.

Cited by 0

Distributed Computing Column 78

Dan Alistarh · ACM SIGACT News · 2020

Overview. In this edition of the column, we have a fascinating contribution by Sergio Rajsbaum and Michel Raynal, who provide an in-depth survey of how our understanding of concurrency has evolved over the past sixty years.

Cited by 1

High Performance Distributed Computing

2004

High Performance Distributed Computing (HPDC) is driven by t h e rapid advance of two related technologies|those underlying computing and communications, respectively.These technology pushes are linked to application pulls, which v ary from the use of a cluster of some 20 workstations simulating uid ow around an aircraft, to the complex linkage of several hundred million advanced PCs around the globe to deliver and receive m ultimedia information.The review of base technologies and exemplar applications is followed by a brief discussion of software models for HPDC, which are illustrated by t wo extremes| PVM and the conjectured future World Wide Web based WebWork concept.The narrative is supplemented by a glossary describing the diverse concepts used in HPDC.

Cited by 12

Distributed and Mobile Computing

Douglas M. Johnston, Michael F. Goodchild, David Maguire et al. · 2004

Technology is moving rapidly to the point where computing will be available everywhere, will be fully mobile, and will provide access to widely distributed resources.This trend to itinerant, distributed, and ubiquitous computing is the latest in a long series of major architectural changes, with associated implications for where computing is performed.Production of geographic data is similarly moving to a new set of arrangements focused on local agencies and individuals.These changes are placed within an economic framework, as a basis for development of a new set of theoretical principles regarding the location of computing, and its implications for geographic information science.Digital libraries are a further instance of these trends, with associated implications for the spatial organization of libraries.The chapter ends by identifying a series of research issues, and the benefits that can be anticipated if these issues are solved.

Cited by 8

Efficient Distributed Quantum Computing

Beals, Robert, Brierley, Stephen, Gray, Oliver et al. · arXiv (Cornell University) · 2012

We provide algorithms for efficiently addressing quantum memory in parallel. These imply that the standard circuit model can be simulated with low overhead by the more realistic model of a distributed quantum computer. As a result, the circuit model can be used by algorithm designers without worrying whether the underlying architecture supports the connectivity of the circuit. In addition, we apply our results to existing memory intensive quantum algorithms. We present a parallel quantum search algorithm and improve the time-space trade-off for the Element Distinctness and Collision problems.

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