Advances and problems in the field of compiler compilers are the subject of the 2nd CCHSC Workshop which took place in Berlin, GDR, in October 1988. The 18 papers which were selected for the workshop are now included in this volume, among them three invited papers. They discuss the requirements, properties and theoretical aspects of compiler compilers as well as tools and metatools for software engineering. The papers cover a wide spectrum in the field of compiler compilers ranging from overviews of existing compiler compilers and engineering of compiler compilers to special problems of attribute evaluation generation and code generation. In connection with compiler compiler projects means of supporting high speed compilation are pointed out. Special attention is given to problems of incremental compilation.
Advances and problems in the field of compiler compilers are considered in this volume, which presents the proceedings of the third in a series of biannual workshops on compiler compilers. Selected papers address the topics of requirements, properties, and theoretical aspects of compiler compilers as well as tools and metatools for software engineering. The 23 papers cover a wide spectrum in the field of compiler compilers, ranging from overviews of new compiler compilers for generating quality compilers to special problems of code generation and optimization. Aspects of compilers for parallel systems and knowledge-based development tools are also discussed.
Despite using them every day, most software engineers know little about how programming languages are designed and implemented. For many, their only experience with that corner of computer science was a terrifying "compilers" class that they suffered through in undergrad and tried to blot from their memory as soon as they had scribbled their last NFA to DFA conversion on the final exam. That fearsome reputation belies a field that is rich with useful techniques and not so difficult as some of its practitioners might have you believe. A better understanding of how programming languages are built will make you a stronger software engineer and teach you concepts and data structures you'll use the rest of your coding days. You might even have fun. This book teaches you everything you need to know to implement a full-featured, efficient scripting language. You'll learn both high-level concepts around parsing and semantics and gritty details like bytecode representation and garbage collection. Your brain will light up with new ideas, and your hands will get dirty and calloused. Starting from main(), you will build a language that features rich syntax, dynamic typing, garbage collection, lexical scope, first-class functions, closures, classes, and inheritance. All packed into a few thousand lines of clean, fast code that you thoroughly understand because you wrote each one yourself.
Significant research activity has occurred in the area of global optimization in recent years. Many new theoretical, algorithmic, and computational contributions have resulted. Despite the major importance of test problems for researchers, there has been a lack of representative nonconvex test problems for constrained global optimization algorithms. This book is motivated by the scarcity of global optimization test problems and represents the first systematic collection of test problems for evaluating and testing constrained global optimization algorithms. This collection includes problems arising in a variety of engineering applications, and test problems from published computational reports.
This book constitutes revised selected papers from 10 workshops that were held as the ISC High Performance 2017 conference in Frankfurt, Germany, in June 2017. The 59 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They stem from the following workshops: Workshop on Virtualization in High-Performance Cloud Computing (VHPC) Visualization at Scale: Deployment Case Studies and Experience Reports International Workshop on Performance Portable Programming Models for Accelerators (P^3MA) OpenPOWER for HPC (IWOPH) International Workshop on Data Reduction for Big Scientific Data (DRBSD) International Workshop on Communication Architectures for HPC, Big Data, Deep Learning and Clouds at Extreme Scale Workshop on HPC Computing in a Post Moore's Law World (HCPM) HPC I/O in the Data Center ( HPC-IODC) Workshop on Performance and Scalability of Storage Systems (WOPSSS) IXPUG: Experiences on Intel Knights Landing at the One Year Mark International Workshop on Communication Architectures for HPC, Big Data, Deep Learning and Clouds at Extreme Scale (ExaComm)
“This book represents a thorough and extensive treatment of the software build process including the choices, benefits, and challenges of a well designed build process. I recommend it not only to all software build engineers but to all software developers since a well designed build process is key to an effective software development process.” —Kevin Bodie, Director Software Development, Pitney Bowes Inc. “An excellent and detailed explanation of build systems, an important but often overlooked part of software development projects. The discussion of productivity as related to build systems is, alone, well worth the time spent reading this book.” —John M. Pantone, Objectech Corporation, VP, IT Educator and Course Developer “Peter Smith provides an interesting and accessible look into the world of software build systems, distilling years of experience and covering virtually every type of tool in the build engineer’s toolbox. Well organized, well written, and very thorough; I would recommend this book to anyone with a build system under their responsibility.” —Jeff Overbey, Project Co-Lead, Photran “Software Build Systems teaches how to think about building software. It surveys the tools and techniques for building software products and the ways things go wrong. This book will appeal to those new to build systems as well as experienced build system engineers.” —Monte Davidoff, Software Development Consultant, Alluvial Software, Inc. Inadequate build systems can dramatically impact developer productivity. Bad dependencies, false compile errors, failed software images, slow compilation, and time-wasting manual processes are just some of the byproducts of a subpar build system. In Software Build Systems, software productivity expert Peter Smith shows you how to implement build systems that overcome all these problems, so you can deliver reliable software more rapidly, at lower cost. Smith explains the core principles underlying highly efficient build systems, surveying both system features and usage scenarios. Next, he encapsulates years of experience in creating and maintaining diverse build systems–helping you make well-informed choices about tools and practices, and avoid common traps and pitfalls. Throughout, he shares a wide range of practical examples and lessons from multiple environments, including Java, C++, C, and C#. Coverage includes • Mastering build system concepts, including source trees, build tools, and compilation tools • Comparing five leading build tools: GNU Make, Ant, SCons, CMake, and the Eclipse IDE’s integrated build features • Ensuring accurate dependency checking and efficient incremental compilation • Using metadata to assist debugging, profiling, and source code documentation • Packaging software for installation on your target machine • Best practices for managing complex version-control systems, build machines, and compilation tools If you’re a developer, this book will illuminate the issues involved in building and maintaining the build system that’s best for your team. If you’re a manager, you’ll discover how to evaluate your team’s build system and improve its effectiveness. And if you’re a build “guru,” you’ll learn how to optimize the performance and scalability of your build system, no matter how demanding your requirements are.
As an outcome of the author's many years of study, teaching, and research in the field of Compilers, and his constant interaction with students, this well-written book magnificently presents both the theory and the design techniques used in Compiler Designing. The book introduces the readers to compilers and their design challenges and describes in detail the different phases of a compiler. The book acquaints the students with the tools available in compiler designing. As the process of compiler designing essentially involves a number of subjects such as Automata Theory, Data Structures, Algorithms, Computer Architecture, and Operating System, the contributions of these fields are also emphasized. Various types of parsers are elaborated starting with the simplest ones such as recursive descent and LL to the most intricate ones such as LR, canonical LR, and LALR, with special emphasis on LR parsers. The new edition introduces a section on Lexical Analysis discussing the optimization techniques for the Deterministic Finite Automata (DFA) and a complete chapter on Syntax-Directed Translation, followed in the compiler design process. Designed primarily to serve as a text for a one-semester course in Compiler Design for undergraduate and postgraduate students of Computer Science, this book would also be of considerable benefit to the professionals. KEY FEATURES • This book is comprehensive yet compact and can be covered in one semester. • Plenty of examples and diagrams are provided in the book to help the readers assimilate the concepts with ease. • The exercises given in each chapter provide ample scope for practice. • The book offers insight into different optimization transformations. • Summary, at end of each chapter, enables the students to recapitulate the topics easily. TARGET AUDIENCE • BE/B.Tech/M.Tech: CSE/IT • M.Sc (Computer Science)
Learn how to use Python to create efficient applications About This Book Identify the bottlenecks in your applications and solve them using the best profiling techniques Write efficient numerical code in NumPy, Cython, and Pandas Adapt your programs to run on multiple processors and machines with parallel programming Who This Book Is For The book is aimed at Python developers who want to improve the performance of their application. Basic knowledge of Python is expected What You Will Learn Write efficient numerical code with the NumPy and Pandas libraries Use Cython and Numba to achieve native performance Find bottlenecks in your Python code using profilers Write asynchronous code using Asyncio and RxPy Use Tensorflow and Theano for automatic parallelism in Python Set up and run distributed algorithms on a cluster using Dask and PySpark In Detail Python is a versatile language that has found applications in many industries. The clean syntax, rich standard library, and vast selection of third-party libraries make Python a wildly popular language. Python High Performance is a practical guide that shows how to leverage the power of both native and third-party Python libraries to build robust applications. The book explains how to use various profilers to find performance bottlenecks and apply the correct algorithm to fix them. The reader will learn how to effectively use NumPy and Cython to speed up numerical code. The book explains concepts of concurrent programming and how to implement robust and responsive applications using Reactive programming. Readers will learn how to write code for parallel architectures using Tensorflow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. By the end of the book, readers will have learned to achieve performance and scale from their Python applications. Style and approach A step-by-step practical guide filled with real-world use cases and examples
