Автор: Hennessy, John Название: Computer Architecture 6 ed. ISBN: 0128119055 ISBN-13(EAN): 9780128119051 Издательство: Elsevier Science Рейтинг: Цена: 14483.00 р. Наличие на складе: Есть (1 шт.) Описание:
Computer Architecture: A Quantitative Approach, Sixth Edition has been considered essential reading by instructors, students and practitioners of computer design for over 20 years. The sixth edition of this classic textbook from Hennessy and Patterson, winners of the 2017 ACM A.M. Turing Award recognizing contributions of lasting and major technical importance to the computing field, is fully revised with the latest developments in processor and system architecture. The text now features examples from the RISC-V (RISC Five) instruction set architecture, a modern RISC instruction set developed and designed to be a free and openly adoptable standard. It also includes a new chapter on domain-specific architectures and an updated chapter on warehouse-scale computing that features the first public information on Google's newest WSC.
True to its original mission of demystifying computer architecture, this edition continues the longstanding tradition of focusing on areas where the most exciting computing innovation is happening, while always keeping an emphasis on good engineering design.
Winner of a 2019 Textbook Excellence Award (Texty) from the Textbook and Academic Authors Association
Includes a new chapter on domain-specific architectures, explaining how they are the only path forward for improved performance and energy efficiency given the end of Moore's Law and Dennard scaling
Features the first publication of several DSAs from industry
Features extensive updates to the chapter on warehouse-scale computing, with the first public information on the newest Google WSC
Offers updates to other chapters including new material dealing with the use of stacked DRAM; data on the performance of new NVIDIA Pascal GPU vs. new AVX-512 Intel Skylake CPU; and extensive additions to content covering multicore architecture and organization
Includes "Putting It All Together" sections near the end of every chapter, providing real-world technology examples that demonstrate the principles covered in each chapter
Includes review appendices in the printed text and additional reference appendices available online
Includes updated and improved case studies and exercises
ACM named John L. Hennessy and David A. Patterson, recipients of the 2017 ACM A.M. Turing Award for pioneering a systematic, quantitative approach to the design and evaluation of computer architectures with enduring impact on the microprocessor industry
Описание: Presemts research on integrating a digital environment in professional settings through IoT design and virtual reality. While highlighting topics such as sensor networks, deep learning techniques, and knowledge management, this publication explores developing methods of smart security as well as protocol support in IoT devices.
Описание: Presemts research on integrating a digital environment in professional settings through IoT design and virtual reality. While highlighting topics such as sensor networks, deep learning techniques, and knowledge management, this publication explores developing methods of smart security as well as protocol support in IoT devices.
This book describes five qualitative investment decision-making methods based on the hesitant fuzzy information. They are: (1) the investment decision-making method based on the asymmetric hesitant fuzzy sigmoid preference relations, (2) the investment decision-making method based on the hesitant fuzzy trade-off and portfolio selection, (3) the investment decision-making method based on the hesitant fuzzy preference envelopment analysis, (4) the investment decision-making method based on the hesitant fuzzy peer-evaluation and strategy fusion, and (5) the investment decision-making method based on the EHVaR measurement and tail analysis.
Описание: The book includes topics, such as: path planning, avoiding obstacles, following the path, go-to-goal control, localization, and visual-based motion control. Four different control algorithms, Type-1 fuzzy logic, Type-2 Fuzzy Logic, Decision Tree Control, and Gaussian Control have been used in overall system design.
Автор: B. S.P. Mishra; Satchidananda Dehuri; Euiwhan Kim; Название: Techniques and Environments for Big Data Analysis ISBN: 3319275186 ISBN-13(EAN): 9783319275185 Издательство: Springer Рейтинг: Цена: 16979.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume is aiming at a wide range of readers andresearchers in the area of Big Data by presenting the recent advances in the fieldsof Big Data Analysis, as well as the techniques and tools used to analyze it.
Описание: This volume presents meta-heuristics approaches for Grid scheduling problems. It brings new ideas, analysis, implementations and evaluation of meta-heuristic techniques for Grid scheduling, which make this volume novel in several aspects.
Автор: Ronald W. Morrison Название: Designing Evolutionary Algorithms for Dynamic Environments ISBN: 364205952X ISBN-13(EAN): 9783642059520 Издательство: Springer Рейтинг: Цена: 10754.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The robust capability of evolutionary algorithms (EAs) to find solutions to difficult problems has permitted them to become popular as optimization and search techniques for many industries. Despite the success of EAs, the resultant solutions are often fragile and prone to failure when the problem changes, usually requiring human intervention to keep the EA on track. Since many optimization problems in engineering, finance, and information technology require systems that can adapt to changes over time, it is desirable that EAs be able to respond to changes in the environment on their own. This book provides an analysis of what an EA needs to do to automatically and continuously solve dynamic problems, focusing on detecting changes in the problem environment and responding to those changes. In this book we identify and quantify a key attribute needed to improve the detection and response performance of EAs in dynamic environments. We then create an enhanced EA, designed explicitly to exploit this new understanding. This enhanced EA is shown to have superior performance on some types of problems. Our experiments evaluating this enhanced EA indicate some pre- viously unknown relationships between performance and diversity that may lead to general methods for improving EAs in dynamic environments. Along the way, several other important design issues are addressed involving com- putational efficiency, performance measurement, and the testing of EAs in dynamic environments.
The virtual penetrating the physical and the implication for augmented reality head-up displays.- Application of wearable technology for the acquisition of learning motivation in an adaptive e-learning platform .- Using non-invasive wearable sensors to estimate perceived fatigue level in manual material handling tasks.- Determination of cognitive assistance functions for manual assembly systems.- Laboratory experiment on visual attention of pedestrians while using twitter and line with a smartphone on a treadmill.- Impressions and congruency of pictures and voices of characters in "The Idolmaster".- Enhancing usability and user experience of children learning by playing games
Автор: Sedighi Art, Smith Milton Название: Fair Scheduling in High Performance Computing Environments ISBN: 3030145670 ISBN-13(EAN): 9783030145675 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces a new scheduler to fairly and efficiently distribute system resources to many users of varying usage patterns compete for them in large shared computing environments. The Rawlsian Fair scheduler developed for this effort is shown to boost performance while reducing delay in high performance computing workloads of certain types including the following four types examined in this book:i. Class A – similar but complementary workloadsii. Class B – similar but steady vs intermittent workloadsiii. Class C – Large vs small workloadsiv. Class D – Large vs noise-like workloadsThis new scheduler achieves short-term fairness for small timescale demanding rapid response to varying workloads and usage profiles. Rawlsian Fair scheduler is shown to consistently benefit workload Classes C and D while it only benefits Classes A and B workloads where they become disproportionate as the number of users increases.A simulation framework, dSim, simulates the new Rawlsian Fair scheduling mechanism. The dSim helps achieve instantaneous fairness in High Performance Computing environments, effective utilization of computing resources, and user satisfaction through the Rawlsian Fair scheduler.
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