Large Scale Numerical Optimization
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Large Scale Numerical Optimization Introduction And Overview
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Author : Cornell University. Dept. of Computer Science
language : en
Publisher:
Release Date : 1991
Large Scale Numerical Optimization Introduction And Overview written by Cornell University. Dept. of Computer Science and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Mathematical optimization categories.
We give an introductory overview of the field of large-scale numerical optimization; some of the basic research issues and recent developments are described. Our emphasisis on methods, techniques, and practical concerns. We hope this article will be of interest to both users and students of numerical optimization.
Large Scale Numerical Optimization
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Author : Thomas Frederick Coleman
language : en
Publisher: SIAM
Release Date : 1990-01-01
Large Scale Numerical Optimization written by Thomas Frederick Coleman and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990-01-01 with Mathematics categories.
Papers from a workshop held at Cornell University, Oct. 1989, and sponsored by Cornell's Mathematical Sciences Institute. Annotation copyright Book News, Inc. Portland, Or.
Large Scale Convex Optimization
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Author : Ernest K. Ryu
language : en
Publisher: Cambridge University Press
Release Date : 2022-12
Large Scale Convex Optimization written by Ernest K. Ryu and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12 with Mathematics categories.
A unified analysis of first-order optimization methods, including parallel-distributed algorithms, using monotone operators.
Applied Machine Learning And High Performance Computing On Aws
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Author : Mani Khanuja
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-12-30
Applied Machine Learning And High Performance Computing On Aws written by Mani Khanuja and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-30 with Computers categories.
Build, train, and deploy large machine learning models at scale in various domains such as computational fluid dynamics, genomics, autonomous vehicles, and numerical optimization using Amazon SageMaker Key FeaturesUnderstand the need for high-performance computing (HPC)Build, train, and deploy large ML models with billions of parameters using Amazon SageMakerLearn best practices and architectures for implementing ML at scale using HPCBook Description Machine learning (ML) and high-performance computing (HPC) on AWS run compute-intensive workloads across industries and emerging applications. Its use cases can be linked to various verticals, such as computational fluid dynamics (CFD), genomics, and autonomous vehicles. This book provides end-to-end guidance, starting with HPC concepts for storage and networking. It then progresses to working examples on how to process large datasets using SageMaker Studio and EMR. Next, you'll learn how to build, train, and deploy large models using distributed training. Later chapters also guide you through deploying models to edge devices using SageMaker and IoT Greengrass, and performance optimization of ML models, for low latency use cases. By the end of this book, you'll be able to build, train, and deploy your own large-scale ML application, using HPC on AWS, following industry best practices and addressing the key pain points encountered in the application life cycle. What you will learnExplore data management, storage, and fast networking for HPC applicationsFocus on the analysis and visualization of a large volume of data using SparkTrain visual transformer models using SageMaker distributed trainingDeploy and manage ML models at scale on the cloud and at the edgeGet to grips with performance optimization of ML models for low latency workloadsApply HPC to industry domains such as CFD, genomics, AV, and optimizationWho this book is for The book begins with HPC concepts, however, it expects you to have prior machine learning knowledge. This book is for ML engineers and data scientists interested in learning advanced topics on using large datasets for training large models using distributed training concepts on AWS, deploying models at scale, and performance optimization for low latency use cases. Practitioners in fields such as numerical optimization, computation fluid dynamics, autonomous vehicles, and genomics, who require HPC for applying ML models to applications at scale will also find the book useful.
Iciam 91
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Author : Robert E. O'Malley
language : en
Publisher: SIAM
Release Date : 1992-01-01
Iciam 91 written by Robert E. O'Malley and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-01-01 with Mathematics categories.
Proceedings -- Computer Arithmetic, Algebra, OOP.
Encyclopedia Of Computer Science And Technology
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Author : Allen Kent
language : en
Publisher: CRC Press
Release Date : 2021-07-28
Encyclopedia Of Computer Science And Technology written by Allen Kent and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-28 with Computers categories.
"This comprehensive reference work provides immediate, fingertip access to state-of-the-art technology in nearly 700 self-contained articles written by over 900 international authorities. Each article in the Encyclopedia features current developments and trends in computers, software, vendors, and applications...extensive bibliographies of leading figures in the field, such as Samuel Alexander, John von Neumann, and Norbert Wiener...and in-depth analysis of future directions."
Online Optimization Of Large Scale Systems
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Author : Martin Grötschel
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-14
Online Optimization Of Large Scale Systems written by Martin Grötschel and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-14 with Mathematics categories.
In its thousands of years of history, mathematics has made an extraordinary ca reer. It started from rules for bookkeeping and computation of areas to become the language of science. Its potential for decision support was fully recognized in the twentieth century only, vitally aided by the evolution of computing and communi cation technology. Mathematical optimization, in particular, has developed into a powerful machinery to help planners. Whether costs are to be reduced, profits to be maximized, or scarce resources to be used wisely, optimization methods are available to guide decision making. Opti mization is particularly strong if precise models of real phenomena and data of high quality are at hand - often yielding reliable automated control and decision proce dures. But what, if the models are soft and not all data are around? Can mathematics help as well? This book addresses such issues, e. g. , problems of the following type: - An elevator cannot know all transportation requests in advance. In which order should it serve the passengers? - Wing profiles of aircrafts influence the fuel consumption. Is it possible to con tinuously adapt the shape of a wing during the flight under rapidly changing conditions? - Robots are designed to accomplish specific tasks as efficiently as possible. But what if a robot navigates in an unknown environment? - Energy demand changes quickly and is not easily predictable over time. Some types of power plants can only react slowly.
Large Scale Computational Problems In Numerical Optimization
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Author :
language : en
Publisher:
Release Date : 2000
Large Scale Computational Problems In Numerical Optimization written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with categories.
Our work under this support broadly falls into five categories: automatic differentiation, sparsity, constraints, parallel computation, and applications. Automatic Differentiation (AD): We developed strong practical methods for computing sparse Jacobian and Hessian matrices which arise frequently in large scale optimization problems [10,35]. In addition, we developed a novel view of "structure" in applied problems along with AD techniques that allowed for the efficient application of sparse AD techniques to dense, but structured, problems. Our AD work included development of freely available MATLAB AD software. Sparsity: We developed new effective and practical techniques for exploiting sparsity when solving a variety of optimization problems. These problems include: bound constrained problems, robust regression problems, the null space problem, and sparse orthogonal factorization. Our sparsity work included development of freely available and published software [38,39]. Constraints: Effectively handling constraints in large scale optimization remains a challenge. We developed a number of new approaches to constrained problems with emphasis on trust region methodologies. Parallel Computation: Our work included the development of specifically parallel techniques for the linear algebra tasks underpinning optimization algorithms. Our work contributed to the nonlinear least-squares problem, nonlinear equations, triangular systems, orthogonalization, and linear programming. Applications: Our optimization work is broadly applicable across numerous application domains. Nevertheless we have specifically worked in several application areas including molecular conformation, molecular energy minimization, computational finance, and bone remodeling.
Large Scale Optimization
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Author : Vladimir Tsurkov
language : en
Publisher: Springer Science & Business Media
Release Date : 2001-03-31
Large Scale Optimization written by Vladimir Tsurkov and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-03-31 with Computers categories.
Decomposition methods aim to reduce large-scale problems to simpler problems. This monograph presents selected aspects of the dimension-reduction problem. Exact and approximate aggregations of multidimensional systems are developed and from a known model of input-output balance, aggregation methods are categorized. The issues of loss of accuracy, recovery of original variables (disaggregation), and compatibility conditions are analyzed in detail. The method of iterative aggregation in large-scale problems is studied. For fixed weights, successively simpler aggregated problems are solved and the convergence of their solution to that of the original problem is analyzed. An introduction to block integer programming is considered. Duality theory, which is widely used in continuous block programming, does not work for the integer problem. A survey of alternative methods is presented and special attention is given to combined methods of decomposition. Block problems in which the coupling variables do not enter the binding constraints are studied. These models are worthwhile because they permit a decomposition with respect to primal and dual variables by two-level algorithms instead of three-level algorithms. Audience: This book is addressed to specialists in operations research, optimization, and optimal control.
A Subspace Interior And Conjugate Gradient Method For Large Scale Bound Constrained Minimization Problems
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Author : Mary Ann Branch
language : en
Publisher:
Release Date : 1995
A Subspace Interior And Conjugate Gradient Method For Large Scale Bound Constrained Minimization Problems written by Mary Ann Branch and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Conjugate gradient methods categories.