Download or read book Optimizing Parallel Programs Using Composable Locality Models written by Hao Luo and published by . This book was released on 2017 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: "On modern processors, the on-chip cache memory is structured in a hierarchy, in order to accommodate the rapidly growing disparity between processor peak speed and off-chip memory speed. This design makes a program's performance highly correlated with its memory access pattern and where the accessed data are positioned within the hierarchy. Locality analysis is to study such correlation and optimize programs accordingly. However, the existing research effort in locality analysis is rather limited when dealing with contemporary parallel workloads. The performance of these workloads can be significantly influenced by how their threads interactively access data. The state of the art in locality analysis is neither sufficient nor efficient in modeling such interaction. Therefore, in this dissertation, I will present a set of locality models to analyze modern parallel workloads. The new models give insights on how the threads share data on a quantitative basis. They have a common property, composability, which makes predicting cache miss ratio extremely efficient, especially for a large number of thread and data placements. I will also show how these models enable new optimizations that significantly improve the performance of GPU applications and parallel workloads on NUMA systems."--Page x.
Download or read book Optimizing Locality and Parallelism Through Program Reorganization written by Sriram Krishnamoorthy and published by . This book was released on 2008 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Development of scalable application codes requires an understanding and exploitation of the locality and parallelism in the computation. This is typically achieved through optimizations by the programmer to match the application characteristics to the architectural features exposed by the parallel programming model. Partitioned address space programming models such as MPI foist a process-centric view of the parallel system, increasing the complexity of parallel programming. Typical global address space models provide a shared memory view that greatly simplifies programming. But the simplified models abstract away the locality information, precluding optimized implementations. In this work, we present techniques to reorganize program execution to optimize locality and parallelism, with little effort from the programmer. For regular loop-based programs operating on dense multi-dimensional arrays, we propose an automatic parallelization technique that attempts to determine a parallel schedule in which all processes can start execution in parallel. When the concurrent tiled iteration space inhibits such execution, we present techniques to re-enable it. This is an alternative to incurring the pipelined startup overhead in schedules generated by prevalent approaches. For less structured programs, we propose a programming model that exposes multiple levels abstraction to the programmer. These abstractions enable quick prototyping coupled with incremental optimizations. The data abstraction provides a global view of distributed data organized as blocks. A block is a subset of data stored contiguously in a single process' address space. The computation is specified as a collection of tasks operating on the data blocks, with parallelism and dependence being specified between them. When the blocking of the data does not match the required access pattern in the computation, the data needs to be reblocked to improve spatial locality. We develop efficient data layout transformation mechanisms for blocked multi-dimensional arrays. We also present mechanisms for automatic management of load balance, disk I/O, and inter-process communication on computations expressed as sets of independent tasks on blocked data stored on disk.
Download or read book Effective Automatic Parallelization and Locality Optimization Using the Polyhedral Model written by Uday Kumar Reddy Bondhugula and published by . This book was released on 2008 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Multicore processors have now become mainstream. The difficulty of programming these architectures to effectively tap the potential of multiple processing units is well-known. Among several ways of addressing this issue, one of the very promising and simultaneously hard approaches is Automatic Parallelization. This approach does not require any effort on part of the programmer in the process of parallelizing a program. The Polyhedral model for compiler optimization is a powerful mathematical framework based on parametric linear algebra and integer linear programming. It provides an abstraction to represent nested loop computation and its data dependences using integer points in polyhedra. Complex execution-reordering, that can improve performance by parallelization as well as locality enhancement, is captured by affine transformations in the polyhedral model. With several recent advances, the polyhedral model has reached a level of maturity in various aspects -- in particular, as a powerful intermediate representation for performing transformations, and code generation after transformations. However, an approach to automatically find good transformations for communication-optimized coarse-grained parallelization together with locality optimization has been a key missing link. This dissertation presents a new automatic transformation framework that solves the above problem. Our approach works by finding good affine transformations through a powerful and practical linear cost function that enables efficient tiling and fusion of sequences of arbitrarily nested loops. This in turn allows simultaneous optimization for coarse-grained parallelism and locality. Synchronization-free parallelism and pipelined parallelism at various levels can be extracted. The framework can be targeted to different parallel architectures, like general-purpose multicores, the Cell processor, GPUs, or embedded multiprocessor SoCs. The proposed framework has been implemented into a new end-to-end transformation tool, PLUTO, that can automatically generate parallel code from regular C program sections. Experimental results from the implemented system show significant performance improvement for single core and multicore execution over state-of-the-art research compiler frameworks as well as the best native production compilers. For several dense linear algebra kernels, code generated from Pluto beats, by a significant margin, the same kernels implemented with sequences of calls to highly-tuned libraries supplied by vendors. The system also allows empirical optimization to be performed in a much wider context than has been attempted previously. In addition, Pluto can serve as the parallel code generation backend for several high-level domain-specific languages.
Download or read book Pro TBB written by Michael Voss and published by Apress. This book was released on 2019-07-09 with total page 775 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book is a modern guide for all C++ programmers to learn Threading Building Blocks (TBB). Written by TBB and parallel programming experts, this book reflects their collective decades of experience in developing and teaching parallel programming with TBB, offering their insights in an approachable manner. Throughout the book the authors present numerous examples and best practices to help you become an effective TBB programmer and leverage the power of parallel systems. Pro TBB starts with the basics, explaining parallel algorithms and C++'s built-in standard template library for parallelism. You'll learn the key concepts of managing memory, working with data structures and how to handle typical issues with synchronization. Later chapters apply these ideas to complex systems to explain performance tradeoffs, mapping common parallel patterns, controlling threads and overhead, and extending TBB to program heterogeneous systems or system-on-chips. What You'll Learn Use Threading Building Blocks to produce code that is portable, simple, scalable, and more understandableReview best practices for parallelizing computationally intensive tasks in your applications Integrate TBB with other threading packages Create scalable, high performance data-parallel programs Work with generic programming to write efficient algorithms Who This Book Is For C++ programmers learning to run applications on multicore systems, as well as C or C++ programmers without much experience with templates. No previous experience with parallel programming or multicore processors is required.
Download or read book Structured Parallel Programming written by Michael McCool and published by Elsevier. This book was released on 2012-06-25 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Optimizing Parallel Applications written by William Shih-hao Hung and published by . This book was released on 1998 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book written by Foster and published by . This book was released on 2002 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: 国外著名高等院校信息科学与技术优秀教材
Download or read book A Higher Order Theory of Locality and Its Application in Multicore Cache Management written by Xiaoya Xiang and published by . This book was released on 2014 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: "As multi-core processors become commonplace and cloud computing is gaining acceptance, applications are increasingly run in parallel over a shared memory hierarchy. While the traditional machine and program metrics such as miss ratio and reuse distance can precisely characterize the memory performance of a single program, they are not composable and therefore cannot model the dynamic interaction between simultaneously running programs. This dissertation presents an alternative metric called program footprint. Given a program execution, its footprint is the amount of data accessed in a given time period. The footprint is composable-- the aggregate footprint of a set of programs is the sum of the footprint of the individual footprints. The dissertation presents the following techniques: Near real-time footprint measurement, first by using two novel algorithms, one for footprint distribution and the other for footprint average, and then by run-time sampling. Higher order theory of cache locality, which shows that traditional metrics can be derived from the footprint and vice versa. (As a result, previous locality metrics can also be obtained in near real time.) Composable model of cache sharing, by footprint composition, which is faster and simpler to use than previous reuse-distance based models. Cache-conscious task regrouping, which reorganizes a parallel workload to minimize the interference in shared cache. Through these techniques, the dissertation establishes the thesis that program interaction in shared cache can be efficiently and accurately modeled and dynamically optimized"--Page vi-vii.
Download or read book Modeling and Optimization of Parallel and Distributed Embedded Systems written by Arslan Munir and published by John Wiley & Sons. This book was released on 2016-02-08 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the state-of-the-art in research in parallel and distributed embedded systems, which have been enabled by developments in silicon technology, micro-electro-mechanical systems (MEMS), wireless communications, computer networking, and digital electronics. These systems have diverse applications in domains including military and defense, medical, automotive, and unmanned autonomous vehicles. The emphasis of the book is on the modeling and optimization of emerging parallel and distributed embedded systems in relation to the three key design metrics of performance, power and dependability. Key features: Includes an embedded wireless sensor networks case study to help illustrate the modeling and optimization of distributed embedded systems. Provides an analysis of multi-core/many-core based embedded systems to explain the modeling and optimization of parallel embedded systems. Features an application metrics estimation model; Markov modeling for fault tolerance and analysis; and queueing theoretic modeling for performance evaluation. Discusses optimization approaches for distributed wireless sensor networks; high-performance and energy-efficient techniques at the architecture, middleware and software levels for parallel multicore-based embedded systems; and dynamic optimization methodologies. Highlights research challenges and future research directions. The book is primarily aimed at researchers in embedded systems; however, it will also serve as an invaluable reference to senior undergraduate and graduate students with an interest in embedded systems research.
Download or read book The Data Parallel Programming Model written by Guy-Rene Perrin and published by Springer Science & Business Media. This book was released on 1996-09-11 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph-like book assembles the thorougly revised and cross-reviewed lectures given at the School on Data Parallelism, held in Les Menuires, France, in May 1996. The book is a unique survey on the current status and future perspectives of the currently very promising and popular data parallel programming model. Much attention is paid to the style of writing and complementary coverage of the relevant issues throughout the 12 chapters. Thus these lecture notes are ideally suited for advanced courses or self-instruction on data parallel programming. Furthermore, the book is indispensable reading for anybody doing research in data parallel programming and related areas.
Download or read book Optimizing Explicitly Parallel Programs written by Arvind Krishnamurthy (Computer scientist) and published by . This book was released on 1994 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "We present compiler optimization techniques for explicitly parallel programs that communicate through a shared address space. The source programs are written in a single program multiple data (SPMD) style, and our machine target is a multiprocessor with physically distributed memory and hardware or software support for a single address space. The source language involves normal read and write operations on the address space, which correspond either to local memory operations or to communication over an interconnect network. The remote operations result in high latencies, but much of the latency can be overlapped with local computation or initiation of further remote operations. Non-blocking memory operations allow this overlap to be expressed directly. However, overlap is difficult for programmers to do by hand; it can lead to subtle program errors, since the order in which operations complete is no longer obvious. Programmers writing explicitly parallel code expect reads and writes from a single thread to take effect in program order, a property called sequential consistency. The use of non-blocking memory operations might yield executions that violate sequential consistency. We provide a new algorithm for static parallel program analysis to detect memory operations that can safely be made non-blocking. The analysis requires dependency information across and within threads, and builds on earlier work by Shasha and Snir. We improve their results by providing a more efficient algorithm for SPMD programs, and by improving the accuracy of the analysis through the use of synchronization information. Using the results of this analysis, we show how to optimize parallel programs by changing blocking operations into non-blocking ones, performing code motion to increase the time for communication overlap, and caching remote values to eliminate some read accesses entirely. We show the potential payoff from each of our optimizations on real applications, using hand-transformed programs. The experiments are done on a CM-5 multiprocessor using the Split-C runtime system, which provides a software implementation of a global address space and both blocking and non-blocking memory operations."
Download or read book William Horn 1837 1915 Mary Melissa Hill and Their Descendants written by Mary Ann Umberson Brame and published by . This book was released on 1963 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Languages and Compilers for Parallel Computing written by Lawrence Rauchwerger and published by Springer Nature. This book was released on 2019-11-19 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 30th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2017, held in College Station, TX, USA, in October 2017. The 17 full papers presented together with abstracts of 5 keynote talks, 11 invited speakers and 4 poster papers in this volume were carefully reviewed and selected from 26 submissions. LCPC encourages submissions that go outside its original scope of scientific computing to diverse areas that are enable or enhanced by the power of parallel systems such as mobile computing, big data, relevant aspects of machine learning, data centers, cognitive computing, etc. LCPC strongly encourages personal interaction and technical discussions along the initial material.
Download or read book Languages and Compilers for Parallel Computing written by Vikram Adve and published by Springer. This book was released on 2008-08-17 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 20th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2007, held in Urbana, IL, USA, in October 2007. The 23 revised full papers presented were carefully reviewed and selected from 49 submissions. The papers are organized in topical sections on reliability, languages, parallel compiler technology, libraries, run-time systems and performance analysis, and general compiler techniques.
Download or read book Programming Massively Parallel Processors written by David B. Kirk and published by Newnes. This book was released on 2012-12-31 with total page 519 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book High Performance Computing written by Michèle Weiland and published by Springer. This book was released on 2019-06-05 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 34th International Conference on High Performance Computing, ISC High Performance 2019, held in Frankfurt/Main, Germany, in June 2019. The 17 revised full papers presented were carefully reviewed and selected from 70 submissions. The papers cover a broad range of topics such as next-generation high performance components; exascale systems; extreme-scale applications; HPC and advanced environmental engineering projects; parallel ray tracing - visualization at its best; blockchain technology and cryptocurrency; parallel processing in life science; quantum computers/computing; what's new with cloud computing for HPC; parallel programming models for extreme-scale computing; workflow management; machine learning and big data analytics; and deep learning and HPC.
Download or read book Abstract Machine Models for Parallel and Distributed Computing written by M. Kara and published by IOS Press. This book was released on 1996 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract Machine Models have played a profound though frequently unacknowledged role in the development of modern computing systems. They provide a precise definition of vital concepts, allow system complexity to be managed by providing appropriate views of the activity under consideration, enable reasoning about the correctness and quantitative performance of proposed problem solutions, and encourage communication through a common medium of expression. Abstract Models in Parallel and Distributed computing have a particularly important role in the development of contemporary systems, encapsulating and controlling an inherently high degree of complexity. The Parallel and Distributed computing communities have traditionally considered themselves to be separate. However, there is a significant contemporary interest in both of these communities in a common hardware model; a set of workstation-class machines connected by a high-performance network. The traditional Parallel/Distributed distinction therefore appears under threat.
