POSIX多线程程序设计中文版

本书版权属于原作者，本人只是从网络收集到本资源，请勿用作商业用途，本人不承担任何侵权责任。 《C++程序设计语言》（原书第4版）是C++领域最经典的参考书

IT6613编程手册，此文档主要阐述芯片寄存器配置相关内容，配合相应的datasheet，即可满足该芯片开发所需。

Programming the world wide web 第8版

This text develops a comprehensive theory of programming languages based on type systems and structural operational semantics. Language concepts are precisely defined by their static and dynamic semantics, presenting the essential tools both intuitively and rigorously while relying on only elementary mathematics. These tools are used to analyze and prove properties of languages and provide the framework for combining and comparing language features. The broad range of concepts includes fundamental data types such as sums and products, polymorphic and abstract types, dynamic typing, dynamic dispatch, subtyping and refinement types, symbols and dynamic classification, parallelism and cost semantics, and concurrency and distribution. The methods are directly applicable to language implementation, to the development of logics for reasoning about programs, and to the formal verification language properties such as type safety. This thoroughly revised second edition includes exercises at the end of nearly every chapter and a new chapter on type refinements. Table of Contents Part I Judgments and Rules Chapter 1 Abstract Syntax Chapter 2 Inductive Definitions Chapter 3 Hypothetical and General Judgments Part II Statics and Dynamics Chapter 4 Statics Chapter 5 Dynamics Chapter 6 Type Safety Chapter 7 Evaluation Dynamics Part III Total Functions Chapter 8 Function Definitions and Values Chapter 9 System T of Higher-Order Recursion Part IV Finite Data Types Chapter 10 Product Types Chapter 11 Sum Types Part V Types and Propositions Chapter 12 Constructive Logic Chapter 13 Classical Logic Part VI Infinite Data Types Chapter 14 Generic Programming Chapter 15 Inductive and Coinductive Types Part VII Variable Types Chapter 16 System F of Polymorphic Types Chapter 17 Abstract Types Chapter 18 Higher Kinds Part VIII Partiality and Recursive Types Chapter 19 System PCF of Recursive Functions Chapter 20 System FPC of Recursive Types Part IX Dynamic Types Chapter 21 The Untyped λ-Calculus Chapter 22 Dynamic Typing Chapter 23 Hybrid Typing Part X Subtyping Chapter 24 Structural Subtyping Chapter 25 Behavioral Typing Chapter Part XI Dynamic Dispatch Chapter 26 Classes and Methods Chapter 27 Inheritance Part XII Control Flow Chapter 28 Control Stacks Chapter 29 Exceptions Chapter 30 Continuations Part XIII Symbolic Data Chapter 31 Symbols Chapter 32 Fluid Binding Chapter 33 Dynamic Classification Part XIV Mutable State Chapter 34 Modernized Algol Chapter 35 Assignable References Chapter 36 Lazy Evaluation Part XV Parallelism Chapter 37 Nested Parallelism Chapter 38 Futures and Speculations Part XVI Concurrency and Distribution Chapter 39 Process Calculus Chapter 40 Concurrent Algol Chapter 41 Distributed Algol Part XVII Modularity Chapter 42 Modularity and Linking Chapter 43 Singleton Kinds and Subkinding Chapter 44 Type Abstractions and Type Classes Chapter 45 Hierarchy and Parameterization Chapter Part XVIII Equational Reasoning Chapter 46 Equality for System T Chapter 47 Equality for System PCF Chapter 48 Parametricity Chapter 49 Process Equivalence Appendix A Background on Finite Sets

Apress, 2010 ，如何用.net来实现并行计算，本书将带你一探究竟 Parallel programming has been revolutionised in .NET 4 providing, for the first time, a standardised and simplified method for creating robust, scalable and reliable multi-threaded applications. The Parallel Programming features of .NET 4 allow the programmer to create applications that harness the power of multi-core and multi-processor machines. Simpler to use and more powerful than “classic” .NET threads, parallel programming allows the developer to remain focused on the work an application needs to perform. In Pro .NET 4 Parallel Programming in C#, Adam Freeman presents expert advice that guides you through the process of creating concurrent C# applications from the ground up. You’ll be introduced to .NET’s parallel programming features, both old and new, discover the key functionality that has been introduced in .NET 4, and learn how you can take advantage of the power of multi-core and multi-processor machines with ease. Pro .NET 4 Parallel Programming in C# is a reliable companion that will remain with you as you explore the parallel programming universe, elegantly and comprehensively explaining all aspects of parallel programming, guiding you around potential pitfalls and providing clear-cut solutions to the common problems that you will encounter. What you’ll learn * Develop scalable and robust parallel applications in C#. * Design, test and use parallel algorithms and data structures. * Understand and implement common parallel design patterns. * Avoid common anti-patterns and problems. * Use Visual Studio to verify and debug parallel applications. amazon link:http://www.amazon.com/exec/obidos/ASIN/1430229675/buythisbooks-20

游戏编程经典书籍，高清，带目录

用于QT环境的安装软件，调试比特币

本书最近好好地研究过了，这里终于要介绍Andrei Alexandrescu了，他是Real公司的项目经理，是GP模板技术的天才，他的高深模板技术影响 了BOOST以及全世界的模板怪杰，本书中他介绍他的库Loki，虽然库十分激进没有实际用途，当时展现的绚烂的特技令人叹服！同时本书是设计 模式用范型实现的经典展现，以及Policy设计模式在其中的极致应用，直接影响了BOOST的adaptor设计（7个Policy）甚至影响了标准库的智能 指针项目（虽然最后被否认了，当时绝对是完美的实现方法）

Author: Francois Louveaux, John R. Birge Publisher: Springer (2000) Binding: Hardcover, 448 pages pricer: $119.00 ISBN-10: 0387982175 editorialreviews The aim of stochastic programming is to find optimal decisions in problems which involve uncertain data. This field is currently developing rapidly with contributions from many disciplines including operations research, mathematics, and probability. Conversely, it is being applied in a wide variety of subjects ranging from agriculture to financial planning and from industrial engineering to computer networks. This textbook provides a first course in stochastic programming suitable for students with a basic knowledge of linear programming, elementary analysis, and probability. The authors aim to present a broad overview of the main themes and methods of the subject. Its prime goal is to help students develop an intuition on how to model uncertainty into mathematical problems, what uncertainty changes bring to the decision process, and what techniques help to manage uncertainty in solving the problems. The first chapters introduce some worked examples of stochastic programming and demonstrate how a stochastic model is formally built. Subsequent chapters develop the properties of stochastic programs and the basic solution techniques used to solve them. Three chapters cover approximation and sampling techniques and the final chapter presents a case study in depth. A wide range of students from operations research, industrial engineering, and related disciplines will find this a well-paced and wide-ranging introduction to this subject.