Modern computer architectures designed with high-performance microprocessors offer tremendous potential gains in performance over previous designs. Yet their very complexity makes it increasingly difficult to produce efficient code and to realize their full potential. This landmark text from two leaders in the field focuses on the pivotal role that compilers can play in addressing this critical issue.

The basis for all the methods presented in this book is data dependence, a fundamental compiler analysis tool for optimizing programs on high-performance microprocessors and parallel architectures. It enables compiler designers to write compilers that automatically transform simple, sequential programs into forms that can exploit special features of these modern architectures.

The text provides a broad introduction to data dependence, to the many transformation strategies it supports, and to its applications to important optimization problems such as parallelization, compiler memory hierarchy management, and instruction scheduling. The authors demonstrate the importance and wide applicability of dependence-based compiler optimizations and give the compiler writer the basics needed to understand and implement them. They also offer cookbook explanations for transforming applications by hand to computational scientists and engineers who are driven to obtain the best possible performance of their complex applications.

The approaches presented are based on research conducted over the past two decades, emphasizing the strategies implemented in research prototypes at Rice University and in several associated commercial systems. Randy Allen and Ken Kennedy have provided an indispensable resource for researchers, practicing professionals, and graduate students engaged in designing and optimizing compilers for modern computer architectures.
* Offers a guide to the simple, practical algorithms and approaches that are most effective in real-world, high-performance microprocessor and parallel systems.
* Demonstrates each transformation in worked examples.
* Examines how two case study compilers implement the theories and practices described in each chapter.
* Presents the most complete treatment of memory hierarchy issues of any compiler text.
* Illustrates ordering relationships with dependence graphs throughout the book.
* Applies the techniques to a variety of languages, including Fortran 77, C, hardware definition languages, Fortran 90, and High Performance Fortran.
* Provides extensive references to the most sophisticated algorithms known in research.

The AVR RISC Microcontroller Handbook is a comprehensive guide to designing with Atmel's new controller family, which is designed to offer high speed and low power consumption at a lower cost. The main text is divided into three sections: hardware, which covers all internal peripherals; software, which covers programming and the instruction set; and tools, which explains using Atmel's Assembler and Simulator (available on the Web) as well as IAR's C compiler.

Practical guide for advanced hobbyists or design professionals
Development tools and code available on the Web

This book introduces basic computing skills designed for industry professionals without a strong computer science background. Written in an easily accessible manner, and accompanied by a user-friendly website, it serves as a self-study guide to survey data science and data engineering for those who aspire to start a computing career, or expand on their current roles, in areas such as applied statistics, big data, machine learning, data mining, and informatics. The authors draw from their combined experience working at software and social network companies, on big data products at several major online retailers, as well as their experience building big data systems for an AI startup. Spanning from the basic inner workings of a computer to advanced data manipulation techniques, this book opens doors for readers to quickly explore and enhance their computing knowledge. Computing with Data comprises a wide range of computational topics essential for data scientists, analysts, and engineers, providing them with the necessary tools to be successful in any role that involves computing with data. The introduction is self-contained, and chapters progress from basic hardware concepts to operating systems, programming languages, graphing and processing data, testing and programming tools, big data frameworks, and cloud computing. The book is fashioned with several audiences in mind. Readers without a strong educational background in CS--or those who need a refresher--will find the chapters on hardware, operating systems, and programming languages particularly useful. Readers with a strong educational background in CS, but without significant industry background, will find the following chapters especially beneficial: learning R, testing, programming, visualizing and processing data in Python and R, system design for big data, data stores, and software craftsmanship.

The book focuses on analyses that extract the flow of data, which imperative programming hides through its use and reuse of memory in computer systems and compilers. It will detail some program transformations that conserve this data flow and will introduce a family of analyses, called reaching definition analyses, to do this task. In addition, it shows that correctness of program transformations is guaranteed by the conservation of data flow.
Professionals and researchers in software engineering, computer engineering, program design analysis, and compiler design will benefit from its presentation of data-flow methods and memory optimization of compilers.

It is well known that embedded systems have to be implemented efficiently. This requires that processors optimized for certain application domains are used in embedded systems. Such an optimization requires a careful exploration of the design space, including a detailed study of cost/performance tradeoffs. In order to avoid time-consuming assembly language programming during design space exploration, compilers are needed. In order to analyze the effect of various software or hardware configurations on the performance, retargetable compilers are needed that can generate code for numerous different potential hardware configurations. This book provides a comprehensive and up-to-date overview of the fast developing area of retargetable compilers for embedded systems. It describes a large set important tools as well as applications of retargetable compilers at different levels in the design flow. Retargetable Compiler Technology for Embedded Systems is mostly self-contained and requires only fundamental knowledge in software and compiler design. It is intended to be a key reference for researchers and designers working on software, compilers, and processor optimization for embedded systems.

While compilers for high-level programming languages are large complex software systems, they have particular characteristics that differentiate them from other software systems. Their functionality is almost completely well-defined - ideally there exist complete precise descriptions of the source and target languages. Additional descriptions of the interfaces to the operating system, programming system and programming environment, and to other compilers and libraries are often available. The book deals with the optimization phase of compilers. In this phase, programs are transformed in order to increase their efficiency. To preserve the semantics of the programs in these transformations, the compiler has to meet the associated applicability conditions. These are checked using static analysis of the programs. In this book the authors systematically describe the analysis and transformation of imperative and functional programs. In addition to a detailed description of important efficiency-improving transformations, the book offers a concise introduction to the necessary concepts and methods, namely to operational semantics, lattices, and fixed-point algorithms. This book is intended for students of computer science. The book is supported throughout with examples, exercises and program fragments.

Effective compilers allow for a more efficient execution of application programs for a given computer architecture, while well-conceived architectural features can support more effective compiler optimization techniques. A well thought-out strategy of trade-offs between compilers and computer architectures is the key to the successful designing of highly efficient and effective computer systems. From embedded micro-controllers to large-scale multiprocessor systems, it is important to understand the interaction between compilers and computer architectures. The goal of the Annual Workshop on Interaction between Compilers and Computer Architectures (INTERACT) is to promote new ideas and to present recent developments in compiler techniques and computer architectures that enhance each other's capabilities and performance. Interaction Between Compilers and Computer Architectures is an updated and revised volume consisting of seven papers originally presented at the Fifth Workshop on Interaction between Compilers and Computer Architectures (INTERACT-5), which was held in conjunction with the IEEE HPCA-7 in Monterrey, Mexico in 2001. This volume explores recent developments and ideas for better integration of the interaction between compilers and computer architectures in designing modern processors and computer systems. Interaction Between Compilers and Computer Architectures is suitable as a secondary text for a graduate level course, and as a reference for researchers and practitioners in industry.

While compilers for high-level programming languages are large complex software systems, they have particular characteristics that differentiate them from other software systems. Their functionality is almost completely well-defined ideally there exist complete precise descriptions of the source and target languages. Additional descriptions of the interfaces to the operating system, programming system and programming environment, and to other compilers and libraries are often available.

This book deals with the analysis phase of translators for programming languages. It describes lexical, syntactic and semantic analysis, specification mechanisms for these tasks from the theory of formal languages, and methods for automatic generation based on the theory of automata. The authors present a conceptual translation structure, i.e., a division into a set of modules, which transform an input program into a sequence of steps in a machine program, and they then describe the interfaces between the modules. Finally, the structures of real translators are outlined. The book contains the necessary theory and advice for implementation.

This book is intended for students of computer science. The book is supported throughout with examples, exercises and program fragments.

"