Author: Sergei Kurgalin
Publisher: Springer Nature
ISBN: 3030275582
Category : Computers
Languages : en
Pages : 210
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Book Description
The book discusses the fundamentals of high-performance computing. The authors combine visualization, comprehensibility, and strictness in their material presentation, and thus influence the reader towards practical application and learning how to solve real computing problems. They address both key approaches to programming modern computing systems: multithreading-based parallelizing in shared memory systems, and applying message-passing technologies in distributed systems. The book is suitable for undergraduate and graduate students, and for researchers and practitioners engaged with high-performance computing systems. Each chapter begins with a theoretical part, where the relevant terminology is introduced along with the basic theoretical results and methods of parallel programming, and concludes with a list of test questions and problems of varying difficulty. The authors include many solutions and hints, and often sample code.
Author: Thomas Sterling
Publisher: Morgan Kaufmann
ISBN: 032390212X
Category : Computers
Languages : en
Pages : 537
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Book Description
Performance Computing: Modern Systems and Practices is a fully comprehensive and easily accessible treatment of high performance computing, covering fundamental concepts and essential knowledge while also providing key skills training. With this book, students will begin their careers with an understanding of possible directions for future research and development in HPC, domain scientists will learn how to use supercomputers as a key tool in their quest for new knowledge, and practicing engineers will discover how supercomputers can employ HPC systems and methods to the design and simulation of innovative products. This new edition has been fully updated, and has been reorganized and restructured to improve accessibility for undergraduate students while also adding trending content such as machine learning and a new chapter on CUDA. - Covers enabling technologies, system architectures and operating systems, parallel programming languages and algorithms, scientific visualization, correctness and performance debugging tools and methods, GPU accelerators, and big data problems - Provides numerous examples that explore the basics of supercomputing while also providing practical training in the real use of high-end computers - Helps users with informative and practical examples that build knowledge and skills through incremental steps - Features sidebars of background and context to present a live history and culture of this unique field
Author: Victor Eijkhout
Publisher: Lulu.com
ISBN: 1257992546
Category : Computers
Languages : en
Pages : 536
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Book Description
This is a textbook that teaches the bridging topics between numerical analysis, parallel computing, code performance, large scale applications.
Author: Georg Hager
Publisher: CRC Press
ISBN: 1439811938
Category : Computers
Languages : en
Pages : 350
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Book Description
Written by high performance computing (HPC) experts, Introduction to High Performance Computing for Scientists and Engineers provides a solid introduction to current mainstream computer architecture, dominant parallel programming models, and useful optimization strategies for scientific HPC. From working in a scientific computing center, the author
Author: David B. Kirk
Publisher: Newnes
ISBN: 0123914183
Category : Computers
Languages : en
Pages : 519
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Book Description
Programming Massively Parallel Processors: A Hands-on Approach, Second Edition, teaches students how to program massively parallel processors. It offers a detailed discussion of various techniques for constructing parallel programs. Case studies are used to demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This guide shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This revised edition contains more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. It also provides new coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies (on MRI reconstruction and molecular visualization) that explore the latest applications of CUDA and GPUs for scientific research and high-performance computing. This book should be a valuable resource for advanced students, software engineers, programmers, and hardware engineers. - New coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more - Increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism - Two new case studies (on MRI reconstruction and molecular visualization) explore the latest applications of CUDA and GPUs for scientific research and high-performance computing
Author: Micha Gorelick
Publisher: O'Reilly Media
ISBN: 1492054992
Category : Computers
Languages : en
Pages : 469
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Book Description
Your Python code may run correctly, but you need it to run faster. Updated for Python 3, this expanded edition shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. By exploring the fundamental theory behind design choices, High Performance Python helps you gain a deeper understanding of Python’s implementation. How do you take advantage of multicore architectures or clusters? Or build a system that scales up and down without losing reliability? Experienced Python programmers will learn concrete solutions to many issues, along with war stories from companies that use high-performance Python for social media analytics, productionized machine learning, and more. Get a better grasp of NumPy, Cython, and profilers Learn how Python abstracts the underlying computer architecture Use profiling to find bottlenecks in CPU time and memory usage Write efficient programs by choosing appropriate data structures Speed up matrix and vector computations Use tools to compile Python down to machine code Manage multiple I/O and computational operations concurrently Convert multiprocessing code to run on local or remote clusters Deploy code faster using tools like Docker
Author: Robert Robey
Publisher: Simon and Schuster
ISBN: 1638350388
Category : Computers
Languages : en
Pages : 702
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Book Description
Parallel and High Performance Computing offers techniques guaranteed to boost your code’s effectiveness. Summary Complex calculations, like training deep learning models or running large-scale simulations, can take an extremely long time. Efficient parallel programming can save hours—or even days—of computing time. Parallel and High Performance Computing shows you how to deliver faster run-times, greater scalability, and increased energy efficiency to your programs by mastering parallel techniques for multicore processor and GPU hardware. About the technology Write fast, powerful, energy efficient programs that scale to tackle huge volumes of data. Using parallel programming, your code spreads data processing tasks across multiple CPUs for radically better performance. With a little help, you can create software that maximizes both speed and efficiency. About the book Parallel and High Performance Computing offers techniques guaranteed to boost your code’s effectiveness. You’ll learn to evaluate hardware architectures and work with industry standard tools such as OpenMP and MPI. You’ll master the data structures and algorithms best suited for high performance computing and learn techniques that save energy on handheld devices. You’ll even run a massive tsunami simulation across a bank of GPUs. What's inside Planning a new parallel project Understanding differences in CPU and GPU architecture Addressing underperforming kernels and loops Managing applications with batch scheduling About the reader For experienced programmers proficient with a high-performance computing language like C, C++, or Fortran. About the author Robert Robey works at Los Alamos National Laboratory and has been active in the field of parallel computing for over 30 years. Yuliana Zamora is currently a PhD student and Siebel Scholar at the University of Chicago, and has lectured on programming modern hardware at numerous national conferences. Table of Contents PART 1 INTRODUCTION TO PARALLEL COMPUTING 1 Why parallel computing? 2 Planning for parallelization 3 Performance limits and profiling 4 Data design and performance models 5 Parallel algorithms and patterns PART 2 CPU: THE PARALLEL WORKHORSE 6 Vectorization: FLOPs for free 7 OpenMP that performs 8 MPI: The parallel backbone PART 3 GPUS: BUILT TO ACCELERATE 9 GPU architectures and concepts 10 GPU programming model 11 Directive-based GPU programming 12 GPU languages: Getting down to basics 13 GPU profiling and tools PART 4 HIGH PERFORMANCE COMPUTING ECOSYSTEMS 14 Affinity: Truce with the kernel 15 Batch schedulers: Bringing order to chaos 16 File operations for a parallel world 17 Tools and resources for better code
Author: Kuan-Ching Li
Publisher: CRC Press
ISBN: 1000553698
Category : Computers
Languages : en
Pages : 307
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Book Description
In this fast-paced global economy, academia and industry must innovate to evolve and succeed. Today’s researchers and industry experts are seeking transformative technologies to meet the challenges of tomorrow. Cutting-edge technological advances in cybersecurity solutions aid in enabling the security of complex heterogeneous high-performance computing (HPC) environments. On the other hand, HPC facilitates powerful and intelligent innovative models for reducing time to response to identify and resolve a multitude of potential, newly emerging cyberattacks. Cybersecurity and High-Performance Computing Environments provides a collection of the current and emergent research innovations, practices, and applications focusing on the interdependence of cybersecurity and HPC domains for discovering and resolving new emerging cyber-threats. KEY FEATURES Represents a substantial research contribution to the state-of-the-art solutions for addressing the threats to confidentiality, integrity, and availability (CIA triad) in HPC environments Covers the groundbreaking and emergent solutions that utilize the power of the HPC environments to study and understand the emergent, multifaceted, anomalous, and malicious characteristics The content will help university students, researchers, and professionals understand how HPC research fits broader cybersecurity objectives and vice versa.
Author: Toby Velte
Publisher: McGraw Hill Professional
ISBN: 0071626956
Category : Computers
Languages : en
Pages : 353
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Book Description
"The promise of cloud computing is here. These pages provide the 'eyes wide open' insights you need to transform your business." --Christopher Crowhurst, Vice President, Strategic Technology, Thomson Reuters A Down-to-Earth Guide to Cloud Computing Cloud Computing: A Practical Approach provides a comprehensive look at the emerging paradigm of Internet-based enterprise applications and services. This accessible book offers a broad introduction to cloud computing, reviews a wide variety of currently available solutions, and discusses the cost savings and organizational and operational benefits. You'll find details on essential topics, such as hardware, platforms, standards, migration, security, and storage. You'll also learn what other organizations are doing and where they're headed with cloud computing. If your company is considering the move from a traditional network infrastructure to a cutting-edge cloud solution, you need this strategic guide. Cloud Computing: A Practical Approach covers: Costs, benefits, security issues, regulatory concerns, and limitations Service providers, including Google, Microsoft, Amazon, Yahoo, IBM, EMC/VMware, Salesforce.com, and others Hardware, infrastructure, clients, platforms, applications, services, and storage Standards, including HTTP, HTML, DHTML, XMPP, SSL, and OpenID Web services, such as REST, SOAP, and JSON Platform as a Service (PaaS), Software as a Service (SaaS), and Software plus Services (S+S) Custom application development environments, frameworks, strategies, and solutions Local clouds, thin clients, and virtualization Migration, best practices, and emerging standards
Author: George Em Karniadakis
Publisher: Cambridge University Press
ISBN: 110749477X
Category : Computers
Languages : en
Pages : 640
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Book Description
Numerical algorithms, modern programming techniques, and parallel computing are often taught serially across different courses and different textbooks. The need to integrate concepts and tools usually comes only in employment or in research - after the courses are concluded - forcing the student to synthesise what is perceived to be three independent subfields into one. This book provides a seamless approach to stimulate the student simultaneously through the eyes of multiple disciplines, leading to enhanced understanding of scientific computing as a whole. The book includes both basic as well as advanced topics and places equal emphasis on the discretization of partial differential equations and on solvers. Some of the advanced topics include wavelets, high-order methods, non-symmetric systems, and parallelization of sparse systems. The material covered is suited to students from engineering, computer science, physics and mathematics.
