Running in Parallel

Running in Parallel PDF Author: Kara O'Toole Treece
Publisher:
ISBN: 9781737138013
Category :
Languages : en
Pages : 292

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Book Description
Two women. Two worlds. One goal: to stay alive. All Fara wants is to earn enough tips to pay the bills, somehow learn to stand up for herself, and eat a good cheeseburger. What she gets is a federal agent who is convinced she is hiding a dangerous device in her tiny apartment; and a new and unexplainable ability that she really could do without. All Blu wants is to restore democracy to her world, preferably without dying in the process. What she gets is the unwanted attention of two of the most lethal leaders of Jurisdiction; one who wants nothing more than to kill her, and the other...well...it's complicated. Neither woman had 'run for my life' on their to-do list, but you don't always get what you want.

R Programming for Data Science

R Programming for Data Science PDF Author: Roger D. Peng
Publisher:
ISBN: 9781365056826
Category : R (Computer program language)
Languages : en
Pages : 0

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Book Description
Data science has taken the world by storm. Every field of study and area of business has been affected as people increasingly realize the value of the incredible quantities of data being generated. But to extract value from those data, one needs to be trained in the proper data science skills. The R programming language has become the de facto programming language for data science. Its flexibility, power, sophistication, and expressiveness have made it an invaluable tool for data scientists around the world. This book is about the fundamentals of R programming. You will get started with the basics of the language, learn how to manipulate datasets, how to write functions, and how to debug and optimize code. With the fundamentals provided in this book, you will have a solid foundation on which to build your data science toolbox.

GNU Parallel 2018

GNU Parallel 2018 PDF Author: Ole Tange
Publisher: Lulu.com
ISBN: 1387509888
Category : Computers
Languages : en
Pages : 114

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Book Description
GNU Parallel is a UNIX shell tool for running jobs in parallel. Learn how to use GNU Parallel from the developer of GNU Parallel.

Parallel and Concurrent Programming in Haskell

Parallel and Concurrent Programming in Haskell PDF Author: Simon Marlow
Publisher: "O'Reilly Media, Inc."
ISBN: 1449335926
Category : Computers
Languages : en
Pages : 322

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Book Description
If you have a working knowledge of Haskell, this hands-on book shows you how to use the language’s many APIs and frameworks for writing both parallel and concurrent programs. You’ll learn how parallelism exploits multicore processors to speed up computation-heavy programs, and how concurrency enables you to write programs with threads for multiple interactions. Author Simon Marlow walks you through the process with lots of code examples that you can run, experiment with, and extend. Divided into separate sections on Parallel and Concurrent Haskell, this book also includes exercises to help you become familiar with the concepts presented: Express parallelism in Haskell with the Eval monad and Evaluation Strategies Parallelize ordinary Haskell code with the Par monad Build parallel array-based computations, using the Repa library Use the Accelerate library to run computations directly on the GPU Work with basic interfaces for writing concurrent code Build trees of threads for larger and more complex programs Learn how to build high-speed concurrent network servers Write distributed programs that run on multiple machines in a network

React 16 Tooling

React 16 Tooling PDF Author: Adam Boduch
Publisher: Packt Publishing Ltd
ISBN: 1788832086
Category : Computers
Languages : en
Pages : 289

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Book Description
React 16 Tooling covers the most important tools, utilities, and libraries that every React developer needs to know — in detail. Key Features Each chapter presents meta-development solutions to help React developers The tools used are presented in a practical, solution-oriented approach with no fluff The chapters are arranged in a logical order that mirrors a typical React development workflow, but you are free to tweak the approaches discussed to fit your own unique style Book Description React 16 Tooling covers the most important tools, utilities, and libraries that every React developer needs to know — in detail. As React has grown, the amazing toolset around it has also grown, adding features and enhancing the development workflow. Each of these essential tools is presented in a practical manner and in a logical order mirroring the development workflow. These tools will make your development life simpler and happier, enabling you to create better and more performant apps. Adam starts with a hand-picked selection of the best tools for the React 16 ecosystem. For starters, there’s the create-react-app utility that’s officially supported by the React team. Not only does this tool bootstrap your React project for you, it also provides a consistent and stable framework to build upon. The premise is that when you don’t have to think about meta development work, more focus goes into the product itself. Other React tools follow this same approach to automating and improving your development life. Jest makes unit testing quicker. Flow makes catching errors easier. Docker containers make deployment in a stack simpler. Storybook makes developing components straightforward. ESLint makes writing standardized code faster. The React DevTools plugin makes debugging a cinch. React 16 Tooling clears away the barriers so you can focus on developing the good parts. In this book, we’ll look at each of these powerful tools in detail, showing you how to build the perfect React ecosystem to develop your apps within. What you will learn Bootstrap a React application using create-react-app Isolate React component development using Storybook Write effective unit tests for your React components using Jest Ensure that your component code is to standard using ESLint Use browser extensions and built-in component instrumentation to debug React applications Enable type safety in React components with Flowtype Deploy React applications inside a Docker container as part of a larger application stack Who this book is for This book is for React developers of any skill level who want to make their lives easier. It helps to have some familiarity with React, but if you are an experienced web developer looking at React, then this book will show you how to build a resilient toolset around you before you begin.

Introduction to Parallel Programming

Introduction to Parallel Programming PDF Author: Subodh Kumar
Publisher: Cambridge University Press
ISBN: 1009276301
Category : Computers
Languages : en
Pages :

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Book Description
In modern computer science, there exists no truly sequential computing system; and most advanced programming is parallel programming. This is particularly evident in modern application domains like scientific computation, data science, machine intelligence, etc. This lucid introductory textbook will be invaluable to students of computer science and technology, acting as a self-contained primer to parallel programming. It takes the reader from introduction to expertise, addressing a broad gamut of issues. It covers different parallel programming styles, describes parallel architecture, includes parallel programming frameworks and techniques, presents algorithmic and analysis techniques and discusses parallel design and performance issues. With its broad coverage, the book can be useful in a wide range of courses; and can also prove useful as a ready reckoner for professionals in the field.

Programming Massively Parallel Processors

Programming Massively Parallel Processors PDF 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

Parallel and High Performance Computing

Parallel and High Performance Computing PDF 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

Parallel Programming Using C++

Parallel Programming Using C++ PDF Author: Gregory V. Wilson
Publisher: MIT Press
ISBN: 9780262731188
Category : Computers
Languages : en
Pages : 796

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Book Description
Foreword by Bjarne Stroustrup Software is generally acknowledged to be the single greatest obstacle preventing mainstream adoption of massively-parallel computing. While sequential applications are routinely ported to platforms ranging from PCs to mainframes, most parallel programs only ever run on one type of machine. One reason for this is that most parallel programming systems have failed to insulate their users from the architectures of the machines on which they have run. Those that have been platform-independent have usually also had poor performance. Many researchers now believe that object-oriented languages may offer a solution. By hiding the architecture-specific constructs required for high performance inside platform-independent abstractions, parallel object-oriented programming systems may be able to combine the speed of massively-parallel computing with the comfort of sequential programming. Parallel Programming Using C++ describes fifteen parallel programming systems based on C++, the most popular object-oriented language of today. These systems cover the whole spectrum of parallel programming paradigms, from data parallelism through dataflow and distributed shared memory to message-passing control parallelism. For the parallel programming community, a common parallel application is discussed in each chapter, as part of the description of the system itself. By comparing the implementations of the polygon overlay problem in each system, the reader can get a better sense of their expressiveness and functionality for a common problem. For the systems community, the chapters contain a discussion of the implementation of the various compilers and runtime systems. In addition to discussing the performance of polygon overlay, several of the contributors also discuss the performance of other, more substantial, applications. For the research community, the contributors discuss the motivations for and philosophy of their systems. As well, many of the chapters include critiques that complete the research arc by pointing out possible future research directions. Finally, for the object-oriented community, there are many examples of how encapsulation, inheritance, and polymorphism can be used to control the complexity of developing, debugging, and tuning parallel software.

Parallel Programming with Microsoft.NET

Parallel Programming with Microsoft.NET PDF Author: Colin Campbell
Publisher: Microsoft Press
ISBN: 9780735651593
Category : Computers
Languages : en
Pages : 0

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Book Description
The CPU meter shows the problem. One core is running at 100 percent, but all the other cores are idle. Your application is CPU-bound, but you are using only a fraction of the computing power of your multicore system. What next? The answer, in a nutshell, is parallel programming. Where you once would have written the kind of sequential code that is familiar to all programmers, you now find that this no longer meets your performance goals. To use your system's CPU resources efficiently, you need to split your application into pieces that can run at the same time. This is easier said than done. Parallel programming has a reputation for being the domain of experts and a minefield of subtle, hard-to-reproduce software defects. Everyone seems to have a favorite story about a parallel program that did not behave as expected because of a mysterious bug. These stories should inspire a healthy respect for the difficulty of the problems you face in writing your own parallel programs. Fortunately, help has arrived. Microsoft Visual Studio(R) 2010 introduces a new programming model for parallelism that significantly simplifies the job. Behind the scenes are supporting libraries with sophisticated algorithms that dynamically distribute computations on multicore architectures. Proven design patterns are another source of help. A Guide to Parallel Programming introduces you to the most important and frequently used patterns of parallel programming and gives executable code samples for them, using the Task Parallel Library (TPL) and Parallel LINQ (PLINQ).