Loop Parallelization

Loop Parallelization

Author: Utpal Banerjee

Publisher: Springer Science & Business Media

Published: 2013-06-29

Total Pages: 187

ISBN-13: 1475756763

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Automatic transformation of a sequential program into a parallel form is a subject that presents a great intellectual challenge and promises a great practical award. There is a tremendous investment in existing sequential programs, and scientists and engineers continue to write their application programs in sequential languages (primarily in Fortran). The demand for higher speedups increases. The job of a restructuring compiler is to discover the dependence structure and the characteristics of the given machine. Much attention has been focused on the Fortran do loop. This is where one expects to find major chunks of computation that need to be performed repeatedly for different values of the index variable. Many loop transformations have been designed over the years, and several of them can be found in any parallelizing compiler currently in use in industry or at a university research facility. The book series on KappaLoop Transformations for Restructuring Compilerskappa provides a rigorous theory of loop transformations and dependence analysis. We want to develop the transformations in a consistent mathematical framework using objects like directed graphs, matrices, and linear equations. Then, the algorithms that implement the transformations can be precisely described in terms of certain abstract mathematical algorithms. The first volume, Loop Transformations for Restructuring Compilers: The Foundations, provided the general mathematical background needed for loop transformations (including those basic mathematical algorithms), discussed data dependence, and introduced the major transformations. The current volume, Loop Parallelization, builds a detailed theory of iteration-level loop transformations based on the material developed in the previous book.


Loop Tiling for Parallelism

Loop Tiling for Parallelism

Author: Jingling Xue

Publisher: Springer Science & Business Media

Published: 2000-08-31

Total Pages: 284

ISBN-13: 9780792379331

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Loop tiling, as one of the most important compiler optimizations, is beneficial for both parallel machines and uniprocessors with a memory hierarchy. This book explores the use of loop tiling for reducing communication cost and improving parallelism for distributed memory machines. The author provides mathematical foundations, investigates loop permutability in the framework of nonsingular loop transformations, discusses the necessary machineries required, and presents state-of-the-art results for finding communication- and time-minimal tiling choices. Throughout the book, theorems and algorithms are illustrated with numerous examples and diagrams. The techniques presented in Loop Tiling for Parallelism can be adapted to work for a cluster of workstations, and are also directly applicable to shared-memory machines once the machines are modeled as BSP (Bulk Synchronous Parallel) machines. Features and key topics: Detailed review of the mathematical foundations, including convex polyhedra and cones; Self-contained treatment of nonsingular loop transformations, code generation, and full loop permutability; Tiling loop nests by rectangles and parallelepipeds, including their mathematical definition, dependence analysis, legality test, and code generation; A complete suite of techniques for generating SPMD code for a tiled loop nest; Up-to-date results on tile size and shape selection for reducing communication and improving parallelism; End-of-chapter references for further reading. Researchers and practitioners involved in optimizing compilers and students in advanced computer architecture studies will find this a lucid and well-presented reference work with numerous citations to original sources.


Introduction to Parallel Computing

Introduction to Parallel Computing

Author: Wesley Petersen

Publisher: OUP Oxford

Published: 2004-01-08

Total Pages: 278

ISBN-13: 019151361X

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In the last few years, courses on parallel computation have been developed and offered in many institutions in the UK, Europe and US as a recognition of the growing significance of this topic in mathematics and computer science. There is a clear need for texts that meet the needs of students and lecturers and this book, based on the author's lecture at ETH Zurich, is an ideal practical student guide to scientific computing on parallel computers working up from a hardware instruction level, to shared memory machines, and finally to distributed memory machines. Aimed at advanced undergraduate and graduate students in applied mathematics, computer science, and engineering, subjects covered include linear algebra, fast Fourier transform, and Monte-Carlo simulations, including examples in C and, in some cases, Fortran. This book is also ideal for practitioners and programmers.


Shared Memory Parallel Programming with Open MP

Shared Memory Parallel Programming with Open MP

Author:

Publisher: Springer Science & Business Media

Published: 2005-02-09

Total Pages: 157

ISBN-13: 354024560X

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This book constitutes the thoroughly refereed postproceedings of the 5th International Workshop on Open MP Application and Tools, WOMPAT 2004, held in Houston, TX, USA in May 2004. The 12 revised full papers presented were carefully selected during two rounds of reviewing and improvement. The papers are devoted to using Open MP for large scale applications on several computing platforms, consideration of Open MP parallelization strategies, discussion and evaluation of several proposed language features, and compiler and tools technology.


Encyclopedia of Parallel Computing

Encyclopedia of Parallel Computing

Author: David Padua

Publisher: Springer Science & Business Media

Published: 2011-09-08

Total Pages: 2211

ISBN-13: 0387097651

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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


Automatic Parallelization

Automatic Parallelization

Author: Samuel Midkiff

Publisher: Springer Nature

Published: 2022-06-01

Total Pages: 157

ISBN-13: 3031017366

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Compiling for parallelism is a longstanding topic of compiler research. This book describes the fundamental principles of compiling "regular" numerical programs for parallelism. We begin with an explanation of analyses that allow a compiler to understand the interaction of data reads and writes in different statements and loop iterations during program execution. These analyses include dependence analysis, use-def analysis and pointer analysis. Next, we describe how the results of these analyses are used to enable transformations that make loops more amenable to parallelization, and discuss transformations that expose parallelism to target shared memory multicore and vector processors. We then discuss some problems that arise when parallelizing programs for execution on distributed memory machines. Finally, we conclude with an overview of solving Diophantine equations and suggestions for further readings in the topics of this book to enable the interested reader to delve deeper into the field. Table of Contents: Introduction and overview / Dependence analysis, dependence graphs and alias analysis / Program parallelization / Transformations to modify and eliminate dependences / Transformation of iterative and recursive constructs / Compiling for distributed memory machines / Solving Diophantine equations / A guide to further reading


Practical Parallel Programming

Practical Parallel Programming

Author: Barr E. Bauer

Publisher: Academic Press

Published: 2014-06-28

Total Pages: 472

ISBN-13: 0080916457

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This is the book that will teach programmers to write faster, more efficient code for parallel processors. The reader is introduced to a vast array of procedures and paradigms on which actual coding may be based. Examples and real-life simulations using these devices are presented in C and FORTRAN.


Languages and Compilers for Parallel Computing

Languages and Compilers for Parallel Computing

Author: Henry Gordon Dietz

Publisher: Springer

Published: 2003-08-03

Total Pages: 453

ISBN-13: 354035767X

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This book constitutes the thoroughly refereed post-proceedings of the 14th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2001, held in Lexington, KY, USA, in August 1-3, 2001. The 28 revised full papers presented were carefully selected during two rounds of reviewing and improvement. All current issues in parallel processing are addressed, in particular compiler optimization, HP Java programming, power-aware parallel architectures, high performance applications, power management of mobile computers, data distribution, shared memory systems, load balancing, garbage collection, parallel components, job scheduling, dynamic parallelization, cache optimization, specification, and dataflow analysis.


Languages and Compilers for Parallel Computing

Languages and Compilers for Parallel Computing

Author: Lawrence Rauchwerger

Publisher: Springer Science & Business Media

Published: 2004-02-25

Total Pages: 567

ISBN-13: 3540211993

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This book constitutes the thoroughly refereed post-proceedings of the 16th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2003, held in College Station, Texas, USA, in October 2003. The 35 revised full papers presented were selected from 48 submissions during two rounds of reviewing and improvement upon presentation at the workshop. The papers are organized in topical sections on adaptive optimization, data locality, parallel languages, high-level transformations, embedded systems, distributed systems software, low-level transformations, compiling for novel architectures, and optimization infrastructure.


Euro-Par 2010 - Parallel Processing

Euro-Par 2010 - Parallel Processing

Author: Pasqua D'Ambra

Publisher: Springer

Published: 2010-09-02

Total Pages: 625

ISBN-13: 3642152775

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Annotation This book constitutes the refereed proceedings of the 16th International Euro-Par Conference held in Ischia, Italy, in August/September 2010. The 90 revised full papers presented were carefully reviewed and selected from 256 submissions. The papers are organized in topical sections on support tools and environments; performance prediction and evaluation; scheduling and load-balancing; high performance architectures and compilers; parallel and distributed data management; grid, cluster and cloud computing; peer to peer computing; distributed systems and algorithms; parallel and distributed programming; parallel numerical algorithms; multicore and manycore programming; theory and algorithms for parallel computation; high performance networks; and mobile and ubiquitous computing.