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

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.

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.

This book investigates the design of compilers for procedural languages, based on the algebraic laws which these languages satisfy. The particular strategy adopted is to reduce an arbitrary source program to a general normal form, capable of representing an arbitrary target machine. This is achieved by a series of normal form reduction theorems which are proved algebraically from the more basic laws. The normal form and the related reduction theorems can then be instantiated to design compilers for distinct target machines. This constitutes the main novelty of the author's approach to compilation, together with the fact that the entire process is formalised within a single and uniform semantic framework of a procedural language and its algberaic laws. Furthermore, by mechanising the approach using the OBJ3 term rewriting system it is shown that a prototype compiler is developed as a byproduct of its own proof of correctness.

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.

This monograph is concerned with the problem of getting computers to transform formal language definitions into compilers. Its purpose is to demonstrate how certain simple theoretical ideas can be used to generate compilers and even compiler generators. As the title suggests, a realistic assessment of the relationship between the complexity of realistic compilation and the relative simplicity studied in theoretical work is attempted. The monograph contains an overview of existing compiler generators. The CERES '83 compiler generator, developed by Neil D. Jones and the author, is described in detail. The CERES system is based on the idea of composing language definitions and it serves as an example of a powerful novel "bootstrapping" technique by which one can generate compiler generators as well as compilers by considering a compiler generator to be, in a sense which is made mathematically precise, a special kind of compiler. The core of the CERES system is a two-page-long machine generated compiler generator. The approach uses ideas from denotational semantics and many-sorted algebra and connects them with novel ideas about how to treat programs and language definitions as data. Considerable effort has been made to present the necessary theory in a manner suitable for readers who have some practical experience but not necessarily a theoretical background in semantics.

This book is the first comprehensive survey of the field of constraint databases, written by leading researchers. Constraint databases are a fairly new and active area of database research. The key idea is that constraints, such as linear or polynomial equations, are used to represent large, or even infinite, sets in a compact way. The ability to deal with infinite sets makes constraint databases particularly promising as a technology for integrating spatial and temporal data with standard relational databases. Constraint databases bring techniques from a variety of fields, such as logic and model theory, algebraic and computational geometry, as well as symbolic computation, to the design and analysis of data models and query languages.