High Performance Programming for Soft Computing PDF Download

Author: Oscar Humberto Montiel Ross
Publisher: CRC Press
ISBN: 146658601X
Category : Computers
Languages : en
Pages : 378

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Book Description
This book examines the present and future of soft computer techniques. It explains how to use the latest technological tools, such as multicore processors and graphics processing units, to implement highly efficient intelligent system methods using a general purpose computer.

Author: John Levesque
Publisher: CRC Press
ISBN: 1420077066
Category : Computers
Languages : en
Pages : 242

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Book Description
High Performance Computing: Programming and Applications presents techniques that address new performance issues in the programming of high performance computing (HPC) applications. Omitting tedious details, the book discusses hardware architecture concepts and programming techniques that are the most pertinent to application developers for achievi

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: 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: Antonio Esposito
Publisher: Packt Publishing Ltd
ISBN: 1785282638
Category : Computers
Languages : en
Pages : 305

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Book Description
This book will help you understand what "programming for performance" means, and use effective coding patterns and techniques to optimize your .NET applications. You will begin by understanding what "high performance coding" means, and the different performance concerns. You will see how CLR works and get an understanding of concepts such as memory management, garbage collection, and thread life cycles. You will proceed to learn about the theoretical and practical concepts of PLINQ programming. You will also see what Big Data is, and how to architect a Big Data solution to manipulate large datasets. Finally, you will learn how to launch and analyze a profile session and execute tests against a code block or application for performance analysis. By the end of this book, you will have a complete understanding of efficient programming using high-performance techniques, and will able to write highly optimized applications.

Author: Vincent Theron
Publisher: Packt Publishing
ISBN: 9781786466044
Category : Computers
Languages : en
Pages : 274

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Book Description
Write efficient, clean, and powerful Scala code and create high-performing applications that your users will loveAbout This Book*This is the first book that explores Scala performance techniques in depth, including how to benchmark your performance so you can understand where to make gains*It provides a first-principles examination of what performance means in a Scala context*This book was written by industry experts Vincent Theron and Michael DiamantWho This Book Is ForIf you are a Scala developer with experience in programming Scala applications and know the basics in Scala, syntax, and frameworks such as Lift or Play, this book is for you. This book will also be useful if you are a Java developer who is interested in switching to Scala, but you don't want to give up the performance of Java code. No knowledge of anything outside Scala is required.What You Will Learn*Find out about performance and how to evaluate the behavior of an application*Analyze the performance of your application on JVM*Use Scala features to achieve a high performance benchmark for your application*Enhance the performance of your application with the Collection API*Explore asynchronous programming to achieve concurrency and parallelism*Achieve a deeper understanding of high performance using advanced toolsIn DetailScala is a statically and strongly typed language that tries to elegantly blend both functional and object-oriented paradigms. It has experienced growing popularity in the past few years as both an appealing and pragmatic choice to write production-ready software in the functional paradigm. Scala lets you solve problems with less code than the alternatives. However, this programmatic gain can come at the cost of performance if you aren't careful.Scala High Performance Programming is written to arm you with the knowledge you need to create highly efficient, clean Scala applications. Starting with the basics of understanding what performance is in a Scala context, we'll look at how to benchmark your performance so you can see the results of your optimizations in action. We'?ll also take a deep dive into type specialization, concurrency, and parallel programming. By the end of the book, you'll be able to code efficient, optimized, solutions in Scala.

Author: Rainer Keller
Publisher: Springer Science & Business Media
ISBN: 3540685642
Category : Computers
Languages : en
Pages : 203

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Book Description
Developing software for current and especially for future architectures will require knowledge about parallel programming techniques of applications and library p- grammers. Multi-core processors are already available today, and processors with a dozen and more cores are on the horizon. The major driving force in hardware development, the game industry, has - ready shown interest in using parallel programming paradigms, such as OpenMP for further developments. Therefore developers have to be supported in the even more complex task of programming for these new architectures. HLRS has a long-lasting tradition of providing its user community with the most up-to-date software tools. Additionally, important research and development projects are worked on at the center: among the software packages developed are the MPI correctness checker Marmot, the OpenMP validation suite and the M- implementations PACX-MPI and Open MPI. All of these software packages are - ing extended in the context of German and European community research projects, such as ParMA, the InterActive European Grid (I2G) project and the German C- laborative Research Center (Sonderforschungsbereich 716). Furthermore, ind- trial collaborations, i.e. with Intel and Microsoft allow HLRS to get its software production-grade ready. In April 2007, a European project on Parallel Programming for Multi-core - chitectures, in short ParMA was launched, with a major focus on providing and developing tools for parallel programming.

Author: Rajkumar Buyya
Publisher: Prentice Hall
ISBN:
Category : Computers
Languages : en
Pages : 904

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Book Description
An authoritative guide to today's revolution in "commodity supercomputing, " this book brings together more than 100 of the field's leading practitioners, providing a single source for up-to-the-minute information on virtually every key system issue associated with high-performance cluster computing.

Author: James Jeffers
Publisher: Newnes
ISBN: 0124104940
Category : Computers
Languages : en
Pages : 430

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Book Description
Authors Jim Jeffers and James Reinders spent two years helping educate customers about the prototype and pre-production hardware before Intel introduced the first Intel Xeon Phi coprocessor. They have distilled their own experiences coupled with insights from many expert customers, Intel Field Engineers, Application Engineers and Technical Consulting Engineers, to create this authoritative first book on the essentials of programming for this new architecture and these new products. This book is useful even before you ever touch a system with an Intel Xeon Phi coprocessor. To ensure that your applications run at maximum efficiency, the authors emphasize key techniques for programming any modern parallel computing system whether based on Intel Xeon processors, Intel Xeon Phi coprocessors, or other high performance microprocessors. Applying these techniques will generally increase your program performance on any system, and better prepare you for Intel Xeon Phi coprocessors and the Intel MIC architecture. - A practical guide to the essentials of the Intel Xeon Phi coprocessor - Presents best practices for portable, high-performance computing and a familiar and proven threaded, scalar-vector programming model - Includes simple but informative code examples that explain the unique aspects of this new highly parallel and high performance computational product - Covers wide vectors, many cores, many threads and high bandwidth cache/memory architecture

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