Download or read book Design and Implementation of Tool chain Framework to Support OpenMP Single Source Compilation on Cell Platform written by Yi Jiang and published by ProQuest. This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The well-known performance and power bottlenecks in traditional architecture design, in conjunction with the sustained demand for high performance in real world applications, stimulated the creation of new designs that utilize multi-cores in one processor. There are two approaches in multi-core design: homogeneous and heterogeneous. The homogeneous design is based on the replication of simple cores. It is easier for developers to port existing applications to this kind of platform. However, great diversity exists among applications and a homogeneous multi-core chip cannot be optimal for heterogeneous workloads. Therefore, more and more multi-core designs tend to utilize heterogeneous cores and specialized accelerators. The Cell Broadband Engine (CBE) is a representative. Every Cell processor integrates one Power Processing Engine(PPE) core and eight Synergistic Processing Engines (SPE). A PPE core has a traditional memory and cache hierarchy and it accesses memory via caching mechanism. On the other hand, each SPE core only has 256K local storage and accesses its own local storage directly. All data exchange between the SPUs and shared system memory is via high-latency DMA operation. Therefore, this architecture presents great challenges to programmers who want to utilize parallelism: (1) Threads running on PPE are far different from the ones on SPEs, both in capability and ISAs. The users have to take care of programming threads in each ISA, as well as their cooperation and synchronization. (2) The SPE local storage is so limited that SPE code or data may have to be partitioned into overlay sections. Given the explicit memory hierarchy, it is necessary for the programmers to issue DMA instructions at the appropriate time and transfer them to or from system memory. (3) Shared data in SPE code also needs to be loaded from and stored to main memory. The Cell processor can guarantee the coherence for all DMA transactions. However, the user would have the responsibility to keep data coherence among SPE local storage. This thesis is inspired by the Open Opell project whose goal is to develop the GNU-Based OpenMP on the CBE platform and address the challenges mentioned above. Our solution involves the whole tool chain and a runtime system. The CBE programmer can take advantage of the convenience of this abstract share-memory programming model. Specifically, we design and implement single source compilation to attack the first challenge. Then the "ghost" mechanism, which invokes overlays and partition manager libraries, helps to deal with the second challenge. Lastly, we try to tackle the third challenge by the software cache library. In this thesis, we mainly focus on my work in the assembler and linker part of the Open Opell system, which addresses three specific problems: (1) Given a heterogeneous system like CBE, how to support single source compilation? (2) How to design a mechanism to automatically invoke code/data overlays and hide all details to the end-user? (3) How to make the solution and implementation robust and efficient? The main contributions of this thesis are: (1) We have completed the design of interfaces between different phases in toolchain to support single openMP source program compilation. (2) We have designed the "ghost" mechanism to invoke the overlays and hide the details about the overlay to high-level users. It will work with the partition manager run-time library to complete automatic code/data load if needed. (3) We have implemented the proposed design in our Open Opell system in a robust and efficient manner. We will focus on the assembler and linker implementation in this thesis. We have used a series of experiments with several non-trivial benchmarks to prove our claim.

Download or read book Optimization of Checkpointing and Execution Model for an Implementation of OpenMP on Distributed Memory Architectures written by Van Long Tran and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: OpenMP and MPI have become the standard tools to develop parallel programs on shared-memory and distributed-memory architectures respectively. As compared to MPI, OpenMP is easier to use. This is due to the ability of OpenMP to automatically execute code in parallel and synchronize results using its directives, clauses, and runtime functions while MPI requires programmers do all this manually. Therefore, some efforts have been made to port OpenMP on distributed-memory architectures. However, excluding CAPE, no solution has successfully met both requirements: 1) to be fully compliant with the OpenMP standard and 2) high performance. CAPE stands for Checkpointing-Aided Parallel Execution. It is a framework that automatically translates and provides runtime functions to execute OpenMP program on distributed-memory architectures based on checkpointing techniques. In order to execute an OpenMP program on distributed-memory system, CAPE uses a set of templates to translate OpenMP source code to CAPE source code, and then, the CAPE source code is compiled by a C/C++ compiler. This code can be executed on distributed-memory systems under the support of the CAPE framework. Basically, the idea of CAPE is the following: the program first run on a set of nodes on the system, each node being executed as a process. Whenever the program meets a parallel section, the master distributes the jobs to the slave processes by using a Discontinuous Incremental Checkpoint (DICKPT). After sending the checkpoints, the master waits for the returned results from the slaves. The next step on the master is the reception and merging of the resulting checkpoints before injecting them into the memory. For slave nodes, they receive different checkpoints, and then, they inject it into their memory to compute the divided job. The result is sent back to the master using DICKPTs. At the end of the parallel region, the master sends the result of the checkpoint to every slaves to synchronize the memory space of the program as a whole. In some experiments, CAPE has shown very high-performance on distributed-memory systems and is a viable and fully compatible with OpenMP solution. However, CAPE is in the development stage. Its checkpoint mechanism and execution model need to be optimized in order to improve the performance, ability, and reliability. This thesis aims at presenting the approaches that were proposed to optimize and improve checkpoints, design and implement a new execution model, and improve the ability for CAPE. First, we proposed arithmetics on checkpoints, which aims at modeling checkpoint's data structure and its operations. This modeling contributes to optimize checkpoint size and reduces the time when merging, as well as improve checkpoints capability. Second, we developed TICKPT which stands for Time-stamp Incremental Checkpointing as an instance of arithmetics on checkpoints. TICKPT is an improvement of DICKPT. It adds a timestamp to checkpoints to identify the checkpoints order. The analysis and experiments to compare it to DICKPT show that TICKPT do not only provide smaller in checkpoint size, but also has less impact on the performance of the program using checkpointing. Third, we designed and implemented a new execution model and new prototypes for CAPE based on TICKPT. The new execution model allows CAPE to use resources efficiently, avoid the risk of bottlenecks, overcome the requirement of matching the Bernstein's conditions. As a result, these approaches make CAPE improving the performance, ability as well as reliability. Four, Open Data-sharing attributes are implemented on CAPE based on arithmetics on checkpoints and TICKPT. This also demonstrates the right direction that we took, and makes CAPE more complete.

Download or read book Using OpenMP written by Barbara Chapman and published by MIT Press. This book was released on 2007-10-12 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive overview of OpenMP, the standard application programming interface for shared memory parallel computing—a reference for students and professionals. "I hope that readers will learn to use the full expressibility and power of OpenMP. This book should provide an excellent introduction to beginners, and the performance section should help those with some experience who want to push OpenMP to its limits." —from the foreword by David J. Kuck, Intel Fellow, Software and Solutions Group, and Director, Parallel and Distributed Solutions, Intel Corporation OpenMP, a portable programming interface for shared memory parallel computers, was adopted as an informal standard in 1997 by computer scientists who wanted a unified model on which to base programs for shared memory systems. OpenMP is now used by many software developers; it offers significant advantages over both hand-threading and MPI. Using OpenMP offers a comprehensive introduction to parallel programming concepts and a detailed overview of OpenMP. Using OpenMP discusses hardware developments, describes where OpenMP is applicable, and compares OpenMP to other programming interfaces for shared and distributed memory parallel architectures. It introduces the individual features of OpenMP, provides many source code examples that demonstrate the use and functionality of the language constructs, and offers tips on writing an efficient OpenMP program. It describes how to use OpenMP in full-scale applications to achieve high performance on large-scale architectures, discussing several case studies in detail, and offers in-depth troubleshooting advice. It explains how OpenMP is translated into explicitly multithreaded code, providing a valuable behind-the-scenes account of OpenMP program performance. Finally, Using OpenMP considers trends likely to influence OpenMP development, offering a glimpse of the possibilities of a future OpenMP 3.0 from the vantage point of the current OpenMP 2.5. With multicore computer use increasing, the need for a comprehensive introduction and overview of the standard interface is clear. Using OpenMP provides an essential reference not only for students at both undergraduate and graduate levels but also for professionals who intend to parallelize existing codes or develop new parallel programs for shared memory computer architectures.

Download or read book Data Parallel C written by James Reinders and published by Apress. This book was released on 2020-11-19 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to accelerate C++ programs using data parallelism. This open access book enables C++ programmers to be at the forefront of this exciting and important new development that is helping to push computing to new levels. It is full of practical advice, detailed explanations, and code examples to illustrate key topics. Data parallelism in C++ enables access to parallel resources in a modern heterogeneous system, freeing you from being locked into any particular computing device. Now a single C++ application can use any combination of devices—including GPUs, CPUs, FPGAs and AI ASICs—that are suitable to the problems at hand. This book begins by introducing data parallelism and foundational topics for effective use of the SYCL standard from the Khronos Group and Data Parallel C++ (DPC++), the open source compiler used in this book. Later chapters cover advanced topics including error handling, hardware-specific programming, communication and synchronization, and memory model considerations. Data Parallel C++ provides you with everything needed to use SYCL for programming heterogeneous systems. What You'll Learn Accelerate C++ programs using data-parallel programming Target multiple device types (e.g. CPU, GPU, FPGA) Use SYCL and SYCL compilers Connect with computing’s heterogeneous future via Intel’s oneAPI initiative Who This Book Is For Those new data-parallel programming and computer programmers interested in data-parallel programming using C++.

Download or read book Handbook of Open Source Tools written by Sandeep Koranne and published by Springer Science & Business Media. This book was released on 2010-10-17 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Open Source Tools introduces a comprehensive collection of advanced open source tools useful in developing software applications. The book contains information on more than 200 open-source tools which include software construction utilities for compilers, virtual-machines, database, graphics, high-performance computing, OpenGL, geometry, algebra, graph theory , GUIs and more. Special highlights for software construction utilities and application libraries are included. Each tool is covered in the context of a real like application development setting. This unique handbook presents a comprehensive discussion of advanced tools, a valuable asset used by most application developers and programmers; includes a special focus on Mathematical Open Source Software not available in most Open Source Software books, and introduces several tools (eg ACL2, CLIPS, CUDA, and COIN) which are not known outside of select groups, but are very powerful. Handbook of Open Source Tools is designed for application developers and programmers working with Open Source Tools. Advanced-level students concentrating on Engineering, Mathematics and Computer Science will find this reference a valuable asset as well.

Download or read book C Coding Standards written by Herb Sutter and published by Pearson Education. This book was released on 2004-10-25 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: Consistent, high-quality coding standards improve software quality, reduce time-to-market, promote teamwork, eliminate time wasted on inconsequential matters, and simplify maintenance. Now, two of the world's most respected C++ experts distill the rich collective experience of the global C++ community into a set of coding standards that every developer and development team can understand and use as a basis for their own coding standards. The authors cover virtually every facet of C++ programming: design and coding style, functions, operators, class design, inheritance, construction/destruction, copying, assignment, namespaces, modules, templates, genericity, exceptions, STL containers and algorithms, and more. Each standard is described concisely, with practical examples. From type definition to error handling, this book presents C++ best practices, including some that have only recently been identified and standardized-techniques you may not know even if you've used C++ for years. Along the way, you'll find answers to questions like What's worth standardizing--and what isn't? What are the best ways to code for scalability? What are the elements of a rational error handling policy? How (and why) do you avoid unnecessary initialization, cyclic, and definitional dependencies? When (and how) should you use static and dynamic polymorphism together? How do you practice "safe" overriding? When should you provide a no-fail swap? Why and how should you prevent exceptions from propagating across module boundaries? Why shouldn't you write namespace declarations or directives in a header file? Why should you use STL vector and string instead of arrays? How do you choose the right STL search or sort algorithm? What rules should you follow to ensure type-safe code? Whether you're working alone or with others, C++ Coding Standards will help you write cleaner code--and write it faster, with fewer hassles and less frustration.

Download or read book Professional CUDA C Programming written by John Cheng and published by John Wiley & Sons. This book was released on 2014-09-09 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Break into the powerful world of parallel GPU programming with this down-to-earth, practical guide Designed for professionals across multiple industrial sectors, Professional CUDA C Programming presents CUDA -- a parallel computing platform and programming model designed to ease the development of GPU programming -- fundamentals in an easy-to-follow format, and teaches readers how to think in parallel and implement parallel algorithms on GPUs. Each chapter covers a specific topic, and includes workable examples that demonstrate the development process, allowing readers to explore both the "hard" and "soft" aspects of GPU programming. Computing architectures are experiencing a fundamental shift toward scalable parallel computing motivated by application requirements in industry and science. This book demonstrates the challenges of efficiently utilizing compute resources at peak performance, presents modern techniques for tackling these challenges, while increasing accessibility for professionals who are not necessarily parallel programming experts. The CUDA programming model and tools empower developers to write high-performance applications on a scalable, parallel computing platform: the GPU. However, CUDA itself can be difficult to learn without extensive programming experience. Recognized CUDA authorities John Cheng, Max Grossman, and Ty McKercher guide readers through essential GPU programming skills and best practices in Professional CUDA C Programming, including: CUDA Programming Model GPU Execution Model GPU Memory model Streams, Event and Concurrency Multi-GPU Programming CUDA Domain-Specific Libraries Profiling and Performance Tuning The book makes complex CUDA concepts easy to understand for anyone with knowledge of basic software development with exercises designed to be both readable and high-performance. For the professional seeking entrance to parallel computing and the high-performance computing community, Professional CUDA C Programming is an invaluable resource, with the most current information available on the market.

Download or read book Computer Organization and Design RISC V Edition written by David A. Patterson and published by Morgan Kaufmann. This book was released on 2017-05-12 with total page 700 pages. Available in PDF, EPUB and Kindle. Book excerpt: The new RISC-V Edition of Computer Organization and Design features the RISC-V open source instruction set architecture, the first open source architecture designed to be used in modern computing environments such as cloud computing, mobile devices, and other embedded systems. With the post-PC era now upon us, Computer Organization and Design moves forward to explore this generational change with examples, exercises, and material highlighting the emergence of mobile computing and the Cloud. Updated content featuring tablet computers, Cloud infrastructure, and the x86 (cloud computing) and ARM (mobile computing devices) architectures is included. An online companion Web site provides advanced content for further study, appendices, glossary, references, and recommended reading. Features RISC-V, the first such architecture designed to be used in modern computing environments, such as cloud computing, mobile devices, and other embedded systems Includes relevant examples, exercises, and material highlighting the emergence of mobile computing and the cloud

Download or read book Data Intensive Text Processing with MapReduce written by Jimmy Lin and published by Springer Nature. This book was released on 2022-05-31 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. The programming model provides an easy-to-understand abstraction for designing scalable algorithms, while the execution framework transparently handles many system-level details, ranging from scheduling to synchronization to fault tolerance. This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns, which represent general reusable solutions to commonly occurring problems across a variety of problem domains. This book not only intends to help the reader "think in MapReduce", but also discusses limitations of the programming model as well. Table of Contents: Introduction / MapReduce Basics / MapReduce Algorithm Design / Inverted Indexing for Text Retrieval / Graph Algorithms / EM Algorithms for Text Processing / Closing Remarks

Download or read book OpenMP Portable Multi Level Parallelism on Modern Systems written by Kent Milfeld and published by Springer Nature. This book was released on 2020-09-01 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 16th International Workshop on OpenMP, IWOMP 2020, held in Austin, TX, USA, in September 2020. The conference was held virtually due to the COVID-19 pandemic. The 21 full papers presented in this volume were carefully reviewed and selected for inclusion in this book. The papers are organized in topical sections named: performance methodologies; applications; OpenMP extensions; performance studies; tools; NUMA; compilation techniques; heterogeneous computing; and memory. The chapters ‘A Case Study on Addressing Complex Load Imbalance in OpenMP’ and ‘A Study of Memory Anomalies in OpenMP Applications’ are available open access under a Creative Commons Attribution 4.0 License via link.springer.com.

Download or read book Introduction to Parallel Computing written by Ananth Grama and published by Pearson Education. This book was released on 2003 with total page 664 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete source of information on almost all aspects of parallel computing from introduction, to architectures, to programming paradigms, to algorithms, to programming standards. It covers traditional Computer Science algorithms, scientific computing algorithms and data intensive algorithms.

Download or read book High level Synthesis written by Michael Fingeroff and published by Xlibris Corporation. This book was released on 2010 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you an RTL or system designer that is currently using, moving, or planning to move to an HLS design environment? Finally, a comprehensive guide for designing hardware using C++ is here. Michael Fingeroff's High-Level Synthesis Blue Book presents the most effective C++ synthesis coding style for achieving high quality RTL. Master a totally new design methodology for coding increasingly complex designs! This book provides a step-by-step approach to using C++ as a hardware design language, including an introduction to the basics of HLS using concepts familiar to RTL designers. Each chapter provides easy-to-understand C++ examples, along with hardware and timing diagrams where appropriate. The book progresses from simple concepts such as sequential logic design to more complicated topics such as memory architecture and hierarchical sub-system design. Later chapters bring together many of the earlier HLS design concepts through their application in simplified design examples. These examples illustrate the fundamental principles behind C++ hardware design, which will translate to much larger designs. Although this book focuses primarily on C and C++ to present the basics of C++ synthesis, all of the concepts are equally applicable to SystemC when describing the core algorithmic part of a design. On completion of this book, readers should be well on their way to becoming experts in high-level synthesis.

Download or read book Applications Tools and Techniques on the Road to Exascale Computing written by Koen de Bosschere and published by IOS Press. This book was released on 2012 with total page 688 pages. Available in PDF, EPUB and Kindle. Book excerpt: Single processing units have now reached a point where further major improvements in their performance are restricted by their physical limitations. This is causing a slowing down in advances at the same time as new scientific challenges are demanding exascale speed. This has meant that parallel processing has become key to High Performance Computing (HPC). This book contains the proceedings of the 14th biennial ParCo conference, ParCo2011, held in Ghent, Belgium. The ParCo conferences have traditionally concentrated on three main themes: Algorithms, Architectures and Applications. Nowadays though, the focus has shifted from traditional multiprocessor topologies to heterogeneous and manycores, incorporating standard CPUs, GPUs (Graphics Processing Units) and FPGAs (Field Programmable Gate Arrays). These platforms are, at a higher abstraction level, integrated in clusters, grids and clouds. The papers presented here reflect this change of focus. New architectures, programming tools and techniques are also explored, and the need for exascale hardware and software was also discussed in the industrial session of the conference.This book will be of interest to all those interested in parallel computing today, and progress towards the exascale computing of tomorrow.

Download or read book Heterogeneous Computing with OpenCL 2 0 written by David R. Kaeli and published by Morgan Kaufmann. This book was released on 2015-06-18 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Heterogeneous Computing with OpenCL 2.0 teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs). This fully-revised edition includes the latest enhancements in OpenCL 2.0 including: • Shared virtual memory to increase programming flexibility and reduce data transfers that consume resources • Dynamic parallelism which reduces processor load and avoids bottlenecks • Improved imaging support and integration with OpenGL Designed to work on multiple platforms, OpenCL will help you more effectively program for a heterogeneous future. Written by leaders in the parallel computing and OpenCL communities, this book explores memory spaces, optimization techniques, extensions, debugging and profiling. Multiple case studies and examples illustrate high-performance algorithms, distributing work across heterogeneous systems, embedded domain-specific languages, and will give you hands-on OpenCL experience to address a range of fundamental parallel algorithms. Updated content to cover the latest developments in OpenCL 2.0, including improvements in memory handling, parallelism, and imaging support Explanations of principles and strategies to learn parallel programming with OpenCL, from understanding the abstraction models to thoroughly testing and debugging complete applications Example code covering image analytics, web plugins, particle simulations, video editing, performance optimization, and more

Download or read book Dynamically Reconfigurable Systems written by Marco Platzner and published by Springer Science & Business Media. This book was released on 2010-03-10 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamically Reconfigurable Systems is the first ever to focus on the emerging field of Dynamically Reconfigurable Computing Systems. While programmable logic and design-time configurability are well elaborated and covered by various texts, this book presents a unique overview over the state of the art and recent results for dynamic and run-time reconfigurable computing systems. Reconfigurable hardware is not only of utmost importance for large manufacturers and vendors of microelectronic devices and systems, but also a very attractive technology for smaller and medium-sized companies. Hence, Dynamically Reconfigurable Systems also addresses researchers and engineers actively working in the field and provides them with information on the newest developments and trends in dynamic and run-time reconfigurable systems.

Download or read book OpenACC for Programmers written by Sunita Chandrasekaran and published by Addison-Wesley Professional. This book was released on 2017-09-11 with total page 563 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Complete Guide to OpenACC for Massively Parallel Programming Scientists and technical professionals can use OpenACC to leverage the immense power of modern GPUs without the complexity traditionally associated with programming them. OpenACCTM for Programmers is one of the first comprehensive and practical overviews of OpenACC for massively parallel programming. This book integrates contributions from 19 leading parallel-programming experts from academia, public research organizations, and industry. The authors and editors explain each key concept behind OpenACC, demonstrate how to use essential OpenACC development tools, and thoroughly explore each OpenACC feature set. Throughout, you’ll find realistic examples, hands-on exercises, and case studies showcasing the efficient use of OpenACC language constructs. You’ll discover how OpenACC’s language constructs can be translated to maximize application performance, and how its standard interface can target multiple platforms via widely used programming languages. Each chapter builds on what you’ve already learned, helping you build practical mastery one step at a time, whether you’re a GPU programmer, scientist, engineer, or student. All example code and exercise solutions are available for download at GitHub. Discover how OpenACC makes scalable parallel programming easier and more practical Walk through the OpenACC spec and learn how OpenACC directive syntax is structured Get productive with OpenACC code editors, compilers, debuggers, and performance analysis tools Build your first real-world OpenACC programs Exploit loop-level parallelism in OpenACC, understand the levels of parallelism available, and maximize accuracy or performance Learn how OpenACC programs are compiled Master OpenACC programming best practices Overcome common performance, portability, and interoperability challenges Efficiently distribute tasks across multiple processors Register your product at informit.com/register for convenient access to downloads, updates, and/or corrections as they become available.

Download or read book Mastering Cloud Computing written by Rajkumar Buyya and published by Newnes. This book was released on 2013-04-05 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mastering Cloud Computing is designed for undergraduate students learning to develop cloud computing applications. Tomorrow's applications won’t live on a single computer but will be deployed from and reside on a virtual server, accessible anywhere, any time. Tomorrow's application developers need to understand the requirements of building apps for these virtual systems, including concurrent programming, high-performance computing, and data-intensive systems. The book introduces the principles of distributed and parallel computing underlying cloud architectures and specifically focuses on virtualization, thread programming, task programming, and map-reduce programming. There are examples demonstrating all of these and more, with exercises and labs throughout. Explains how to make design choices and tradeoffs to consider when building applications to run in a virtual cloud environment Real-world case studies include scientific, business, and energy-efficiency considerations