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This book explores break-through approaches to tackling and mitigating the well-known problems of compiler optimization using design space exploration and machine learning techniques. It demonstrates that not all the optimization passes are suitable for use within an optimization sequence and that, in fact, many of the available passes tend to counteract one another. After providing a comprehensive survey of currently available methodologies, including many experimental comparisons with state-of-the-art compiler frameworks, the book describes new approaches to solving the problem of selecting the best compiler optimizations and the phase-ordering problem, allowing readers to overcome the enormous complexity of choosing the right order of optimizations for each code segment in an application. As such, the book offers a valuable resource for a broad readership, including researchers interested in Computer Architecture, Electronic Design Automation and Machine Learning, as well as computer architects and compiler developers.
Automatic Performance Tuning is a new software paradigm which enables software to be high performance in any computing environment. Its methodologies have been developed over the past decade, and it is now rapidly growing in terms of its scope and applicability, as well as in its scientific knowledge and technological methods. Software developers and researchers in the area of scientific and technical computing, high performance database systems, optimized compilers, high performance systems software, and low-power computing will find this book to be an invaluable reference to this powerful new paradigm.
This three volume set (CCIS 853-855) constitutes the proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cádiz, Spain, in June 2018. The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe time series; discrete models and computational intelligence; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy logic and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications; mathematical fuzzy logic, mathematical morphology; measures of comparison and entropies for fuzzy sets and their extensions; new trends in data aggregation; pre-aggregation functions and generalized forms of monotonicity; rough and fuzzy similarity modelling tools; soft computing for decision making in uncertainty; soft computing in information retrieval and sentiment analysis; tri-partitions and uncertainty; decision making modeling and applications; logical methods in mining knowledge from big data; metaheuristics and machine learning; optimization models for modern analytics; uncertainty in medicine; uncertainty in Video/Image Processing (UVIP).
This book constitutes the proceedings of the 23rd International Conference on Compiler Construction, CC 2014, which was held as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2014, which took place in Grenoble, France, in April 2014. The 10 full papers and 4 tool papers included in this volume were carefully reviewed and selected from 47 submissions; the book also contains one invited talk. The papers are organized in topical sections named: program analysis and optimization; parallelism and parsing and new trends in compilation.
This book contains extended versions of the best papers presented at the 14th International Conference on Information and Communication Technologies in Education, Research, and Industrial Applications, ICTERI 2018, held in Kyiv, Ukraine, in May 2018. The 14 revised full papers included in this volume along with one invited full paper were carefully reviewed and selected from 257 initial submissions. The papers are organized in the following topical sections: ​advances in ICT research, ICT in education and education management, ICT solutions for industrial applications.
This book constitutes the thoroughly refereed post-conference proceedings of the 34th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2020, held in Delaware, NE, USA, in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 9 revised full papers were carefully reviewed and selected from 11 submissions. The conference covers all aspects of languages, compiler techniques, run-time environments, and compiler-related performance evaluation for parallel and high-performance computing. The scope of the workshop encompasses foundational results, as well as practical experience reports and bold new ideas for future systems.
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.
"Embedded Computing is enthralling in its clarity and exhilarating in its scope. If the technology you are working on is associated with VLIWs or "embedded computing", then clearly it is imperative that you read this book. If you are involved in computer system design or programming, you must still read this book, because it will take you to places where the views are spectacular. You don't necessarily have to agree with every point the authors make, but you will understand what they are trying to say, and they will make you think.” From the Foreword by Robert Colwell, R&E Colwell & Assoc. Inc The fact that there are more embedded computers than general-purpose computers and that we are impacted by hundreds of them every day is no longer news. What is news is that their increasing performance requirements, complexity and capabilities demand a new approach to their design. Fisher, Faraboschi, and Young describe a new age of embedded computing design, in which the processor is central, making the approach radically distinct from contemporary practices of embedded systems design. They demonstrate why it is essential to take a computing-centric and system-design approach to the traditional elements of nonprogrammable components, peripherals, interconnects and buses. These elements must be unified in a system design with high-performance processor architectures, microarchitectures and compilers, and with the compilation tools, debuggers and simulators needed for application development. In this landmark text, the authors apply their expertise in highly interdisciplinary hardware/software development and VLIW processors to illustrate this change in embedded computing. VLIW architectures have long been a popular choice in embedded systems design, and while VLIW is a running theme throughout the book, embedded computing is the core topic. Embedded Computing examines both in a book filled with fact and opinion based on the authors many years of R&D experience. Features: · Complemented by a unique, professional-quality embedded tool-chain on the authors' website, http://www.vliw.org/book · Combines technical depth with real-world experience · Comprehensively explains the differences between general purpose computing systems and embedded systems at the hardware, software, tools and operating system levels. · Uses concrete examples to explain and motivate the trade-offs.
During the last several decades compiler developers have invented a set of powerful heuristics to deal with the complexity of the algorithms they have to use. However, this led to a new problem of finding the best values for every heuristic. This paper describes how machine learning techniques, such as logistic regression, can be used to build a framework for the automatic tuning of compiler heuristics. In this paper we were focused on decreasing the compile time for the static commercial compiler called TPO (Toronto Portable Optimizer) while preserving the execution time. Nevertheless, our techniques can also be used for decreasing the execution time and in dynamic behavior. Our experiments showed that we can speedup the compile process by at least a factor of two with almost the same generated code quality on the SPEC2000 benchmark suite, and that our logistic classifier achieves the same prediction quality for non-SPEC benchmarks.
Heterogeneous Computing Architectures: Challenges and Vision provides an updated vision of the state-of-the-art of heterogeneous computing systems, covering all the aspects related to their design: from the architecture and programming models to hardware/software integration and orchestration to real-time and security requirements. The transitions from multicore processors, GPU computing, and Cloud computing are not separate trends, but aspects of a single trend-mainstream; computers from desktop to smartphones are being permanently transformed into heterogeneous supercomputer clusters. The reader will get an organic perspective of modern heterogeneous systems and their future evolution.