High Performance Compilers For Parallel Computing

Download or read book High Performance Compilers for Parallel Computing written by Michael Joseph Wolfe and published by Addison Wesley. This book was released on 1996 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: Software -- Operating Systems.

Download or read book Languages and Compilers for Parallel Computing written by Santosh Pande and published by Springer. This book was released on 2021-03-26 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 32nd International Workshop on Languages and Compilers for Parallel Computing, LCPC 2019, held in Atlanta, GA, USA, in October 2019. The 8 revised full papers and 3 revised short papers were carefully reviewed and selected from 17 submissions. The scope of the workshop includes advances in programming systems for current domains and platforms, e.g., scientific computing, batch/ streaming/ real-time data analytics, machine learning, cognitive computing, heterogeneous/ reconfigurable computing, mobile computing, cloud computing, IoT, as well as forward-looking computing domains such as analog and quantum computing.

Download or read book High Performance Parallel Runtimes written by Michael Klemm and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-02-08 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the theoretical and practical aspects of parallel programming systems for today's high performance multi-core processors and discusses the efficient implementation of key algorithms needed to implement parallel programming models. Such implementations need to take into account the specific architectural aspects of the underlying computer architecture and the features offered by the execution environment. This book briefly reviews key concepts of modern computer architecture, focusing particularly on the performance of parallel codes as well as the relevant concepts in parallel programming models. The book then turns towards the fundamental algorithms used to implement the parallel programming models and discusses how they interact with modern processors. While the book will focus on the general mechanisms, we will mostly use the Intel processor architecture to exemplify the implementation concepts discussed but will present other processor architectures where appropriate. All algorithms and concepts are discussed in an easy to understand way with many illustrative examples, figures, and source code fragments. The target audience of the book is students in Computer Science who are studying compiler construction, parallel programming, or programming systems. Software developers who have an interest in the core algorithms used to implement a parallel runtime system, or who need to educate themselves for projects that require the algorithms and concepts discussed in this book will also benefit from reading it. You can find the source code for this book at https://github.com/parallel-runtimes/lomp.

Download or read book Introduction to High Performance Scientific Computing written by Victor Eijkhout and published by Lulu.com. This book was released on 2010 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a textbook that teaches the bridging topics between numerical analysis, parallel computing, code performance, large scale applications.

Download or read book Parallel and High Performance Computing written by Robert Robey and published by Simon and Schuster. This book was released on 2021-08-24 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Software Optimization for High-performance Computing written by Kevin R. Wadleigh and published by Prentice Hall Professional. This book was released on 2000 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: The hands-on guide to high-performance coding and algorithm optimization. This hands-on guide to software optimization introduces state-of-the-art solutions for every key aspect of software performance - both code-based and algorithm-based. Two leading HP software performance experts offer comparative optimization strategies for RISC and for the new Explicitly Parallel Instruction Computing (EPIC) design used in Intel IA-64 processors. Using many practical examples, they offer specific techniques for: Predicting and measuring performance - and identifying your best optimization opportunities Storage optimization: cache, system memory, virtual memory, and I/0 Parallel processing: distributed-memory and shared-memory (SMP and ccNUMA) Compilers and loop optimization Enhancing parallelism: compiler directives, threads, and message passing Mathematical libraries and algorithms Whether you're a developer, ISV, or technical researcher, if you need to optimize high-performance software on today's leading processors, one book delivers the advanced techniques and code examples you need: Software Optimization for High Performance Computing.

Download or read book Encyclopedia of Parallel Computing written by David Padua and published by Springer Science & Business Media. This book was released on 2011-09-08 with total page 2211 pages. Available in PDF, EPUB and Kindle. Book excerpt: Containing over 300 entries in an A-Z format, the Encyclopedia of Parallel Computing provides easy, intuitive access to relevant information for professionals and researchers seeking access to any aspect within the broad field of parallel computing. Topics for this comprehensive reference were selected, written, and peer-reviewed by an international pool of distinguished researchers in the field. The Encyclopedia is broad in scope, covering machine organization, programming languages, algorithms, and applications. Within each area, concepts, designs, and specific implementations are presented. The highly-structured essays in this work comprise synonyms, a definition and discussion of the topic, bibliographies, and links to related literature. Extensive cross-references to other entries within the Encyclopedia support efficient, user-friendly searchers for immediate access to useful information. Key concepts presented in the Encyclopedia of Parallel Computing include; laws and metrics; specific numerical and non-numerical algorithms; asynchronous algorithms; libraries of subroutines; benchmark suites; applications; sequential consistency and cache coherency; machine classes such as clusters, shared-memory multiprocessors, special-purpose machines and dataflow machines; specific machines such as Cray supercomputers, IBM’s cell processor and Intel’s multicore machines; race detection and auto parallelization; parallel programming languages, synchronization primitives, collective operations, message passing libraries, checkpointing, and operating systems. Topics covered: Speedup, Efficiency, Isoefficiency, Redundancy, Amdahls law, Computer Architecture Concepts, Parallel Machine Designs, Benmarks, Parallel Programming concepts & design, Algorithms, Parallel applications. This authoritative reference will be published in two formats: print and online. The online edition features hyperlinks to cross-references and to additional significant research. Related Subjects: supercomputing, high-performance computing, distributed computing