High Performance Parallel Runtimes


Book Description

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.




Introduction to High Performance Scientific Computing


Book Description

This is a textbook that teaches the bridging topics between numerical analysis, parallel computing, code performance, large scale applications.




Parallel and High Performance Computing


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




Structured Parallel Programming


Book Description

Programming is now parallel programming. Much as structured programming revolutionized traditional serial programming decades ago, a new kind of structured programming, based on patterns, is relevant to parallel programming today. Parallel computing experts and industry insiders Michael McCool, Arch Robison, and James Reinders describe how to design and implement maintainable and efficient parallel algorithms using a pattern-based approach. They present both theory and practice, and give detailed concrete examples using multiple programming models. Examples are primarily given using two of the most popular and cutting edge programming models for parallel programming: Threading Building Blocks, and Cilk Plus. These architecture-independent models enable easy integration into existing applications, preserve investments in existing code, and speed the development of parallel applications. Examples from realistic contexts illustrate patterns and themes in parallel algorithm design that are widely applicable regardless of implementation technology. The patterns-based approach offers structure and insight that developers can apply to a variety of parallel programming models Develops a composable, structured, scalable, and machine-independent approach to parallel computing Includes detailed examples in both Cilk Plus and the latest Threading Building Blocks, which support a wide variety of computers




Introduction to Parallel Programming


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.




Languages and Compilers for Parallel Computing


Book Description

LCPC’98 Steering and Program Committes for their time and energy in - viewing the submitted papers. Finally, and most importantly, we thank all the authors and participants of the workshop. It is their signi cant research work and their enthusiastic discussions throughout the workshopthat made LCPC’98 a success. May 1999 Siddhartha Chatterjee Program Chair Preface The year 1998 marked the eleventh anniversary of the annual Workshop on Languages and Compilers for Parallel Computing (LCPC), an international - rum for leading research groups to present their current research activities and latest results. The LCPC community is interested in a broad range of te- nologies, with a common goal of developing software systems that enable real applications. Amongthetopicsofinteresttotheworkshoparelanguagefeatures, communication code generation and optimization, communication libraries, d- tributed shared memory libraries, distributed object systems, resource m- agement systems, integration of compiler and runtime systems, irregular and dynamic applications, performance evaluation, and debuggers. LCPC’98 was hosted by the University of North Carolina at Chapel Hill (UNC-CH) on 7 - 9 August 1998, at the William and Ida Friday Center on the UNC-CH campus. Fifty people from the United States, Europe, and Asia attended the workshop. The program committee of LCPC’98, with the help of external reviewers, evaluated the submitted papers. Twenty-four papers were selected for formal presentation at the workshop. Each session was followed by an open panel d- cussion centered on the main topic of the particular session.




Languages and Compilers for Parallel Computing


Book Description

This book constitutes the thoroughly refereed post-proceedings of the 18th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2005, held in Hawthorne, NY, USA in October 2005. The 26 revised full papers and eight short papers presented were carefully selected during two rounds of reviewing and improvement. The papers are organized in topical sections.




Languages and Compilers for Parallel Computing


Book Description

This volume contains the papers presented at the 13th International Workshop on Languages and Compilers for Parallel Computing. It also contains extended abstracts of submissions that were accepted as posters. The workshop was held at the IBM T. J. Watson Research Center in Yorktown Heights, New York. As in previous years, the workshop focused on issues in optimizing compilers, languages, and software environments for high performance computing. This continues a trend in which languages, compilers, and software environments for high performance computing, and not strictly parallel computing, has been the organizing topic. As in past years, participants came from Asia, North America, and Europe. This workshop re?ected the work of many people. In particular, the members of the steering committee, David Padua, Alex Nicolau, Utpal Banerjee, and David Gelernter, have been instrumental in maintaining the focus and quality of the workshop since it was ?rst held in 1988 in Urbana-Champaign. The assistance of the other members of the program committee – Larry Carter, Sid Chatterjee, Jeanne Ferrante, Jans Prins, Bill Pugh, and Chau-wen Tseng – was crucial. The infrastructure at the IBM T. J. Watson Research Center provided trouble-free logistical support. The IBM T. J. Watson Research Center also provided ?nancial support by underwriting much of the expense of the workshop. Appreciation must also be extended to Marc Snir and Pratap Pattnaik of the IBM T. J. Watson Research Center for their support.




Languages and Compilers for Parallel Computing


Book Description

The LNCS series reports state-of-the-art results in computer science research, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and societies, LNCS has grown into the most comprehensive computer science research forum available. The scope of LNCS, including its subseries LNAI and LNBI, spans the whole range of computer science and information technology including interdisciplinary topics in a variety of application fields. In parallel to the printed book, each new volume is published electronically in LNCS Online.