Std::Generator: Synchronous Coroutine Generator for Ranges
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Armadillo C++ Library
Armadillo: a template-based C++ library for linear algebra Conrad Sanderson and Ryan Curtin Abstract The C++ language is often used for implementing functionality that is performance and/or resource sensitive. While the standard C++ library provides many useful algorithms (such as sorting), in its current form it does not provide direct handling of linear algebra (matrix maths). Armadillo is an open source linear algebra library for the C++ language, aiming towards a good balance between speed and ease of use. Its high-level application programming interface (function syntax) is deliberately similar to the widely used Matlab and Octave languages [4], so that mathematical operations can be expressed in a familiar and natural manner. The library is useful for algorithm development directly in C++, or relatively quick conversion of research code into production environments. Armadillo provides efficient objects for vectors, matrices and cubes (third order tensors), as well as over 200 associated functions for manipulating data stored in the objects. Integer, floating point and complex numbers are supported, as well as dense and sparse storage formats. Various matrix factorisations are provided through integration with LAPACK [3], or one of its high performance drop-in replacements such as Intel MKL [6] or OpenBLAS [9]. It is also possible to use Armadillo in conjunction with NVBLAS to obtain GPU-accelerated matrix multiplication [7]. Armadillo is used as a base for other open source projects, such as MLPACK, a C++ library for machine learning and pattern recognition [2], and RcppArmadillo, a bridge between the R language and C++ in order to speed up computations [5]. -
The Early History of Smalltalk
The Early History of Smalltalk http://www.accesscom.com/~darius/EarlyHistoryS... The Early History of Smalltalk Alan C. Kay Apple Computer [email protected]# Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission. HOPL-II/4/93/MA, USA © 1993 ACM 0-89791-571-2/93/0004/0069...$1.50 Abstract Most ideas come from previous ideas. The sixties, particularly in the ARPA community, gave rise to a host of notions about "human-computer symbiosis" through interactive time-shared computers, graphics screens and pointing devices. Advanced computer languages were invented to simulate complex systems such as oil refineries and semi-intelligent behavior. The soon-to- follow paradigm shift of modern personal computing, overlapping window interfaces, and object-oriented design came from seeing the work of the sixties as something more than a "better old thing." This is, more than a better way: to do mainframe computing; for end-users to invoke functionality; to make data structures more abstract. Instead the promise of exponential growth in computing/$/volume demanded that the sixties be regarded as "almost a new thing" and to find out what the actual "new things" might be. For example, one would compute with a handheld "Dynabook" in a way that would not be possible on a shared mainframe; millions of potential users meant that the user interface would have to become a learning environment along the lines of Montessori and Bruner; and needs for large scope, reduction in complexity, and end-user literacy would require that data and control structures be done away with in favor of a more biological scheme of protected universal cells interacting only through messages that could mimic any desired behavior. -
Scala Tutorial
Scala Tutorial SCALA TUTORIAL Simply Easy Learning by tutorialspoint.com tutorialspoint.com i ABOUT THE TUTORIAL Scala Tutorial Scala is a modern multi-paradigm programming language designed to express common programming patterns in a concise, elegant, and type-safe way. Scala has been created by Martin Odersky and he released the first version in 2003. Scala smoothly integrates features of object-oriented and functional languages. This tutorial gives a great understanding on Scala. Audience This tutorial has been prepared for the beginners to help them understand programming Language Scala in simple and easy steps. After completing this tutorial, you will find yourself at a moderate level of expertise in using Scala from where you can take yourself to next levels. Prerequisites Scala Programming is based on Java, so if you are aware of Java syntax, then it's pretty easy to learn Scala. Further if you do not have expertise in Java but you know any other programming language like C, C++ or Python, then it will also help in grasping Scala concepts very quickly. Copyright & Disclaimer Notice All the content and graphics on this tutorial are the property of tutorialspoint.com. Any content from tutorialspoint.com or this tutorial may not be redistributed or reproduced in any way, shape, or form without the written permission of tutorialspoint.com. Failure to do so is a violation of copyright laws. This tutorial may contain inaccuracies or errors and tutorialspoint provides no guarantee regarding the accuracy of the site or its contents including this tutorial. If you discover that the tutorialspoint.com site or this tutorial content contains some errors, please contact us at [email protected] TUTORIALS POINT Simply Easy Learning Table of Content Scala Tutorial .......................................................................... -
Object-Oriented Programming in the Beta Programming Language
OBJECT-ORIENTED PROGRAMMING IN THE BETA PROGRAMMING LANGUAGE OLE LEHRMANN MADSEN Aarhus University BIRGER MØLLER-PEDERSEN Ericsson Research, Applied Research Center, Oslo KRISTEN NYGAARD University of Oslo Copyright c 1993 by Ole Lehrmann Madsen, Birger Møller-Pedersen, and Kristen Nygaard. All rights reserved. No part of this book may be copied or distributed without the prior written permission of the authors Preface This is a book on object-oriented programming and the BETA programming language. Object-oriented programming originated with the Simula languages developed at the Norwegian Computing Center, Oslo, in the 1960s. The first Simula language, Simula I, was intended for writing simulation programs. Si- mula I was later used as a basis for defining a general purpose programming language, Simula 67. In addition to being a programming language, Simula1 was also designed as a language for describing and communicating about sys- tems in general. Simula has been used by a relatively small community for many years, although it has had a major impact on research in computer sci- ence. The real breakthrough for object-oriented programming came with the development of Smalltalk. Since then, a large number of programming lan- guages based on Simula concepts have appeared. C++ is the language that has had the greatest influence on the use of object-oriented programming in industry. Object-oriented programming has also been the subject of intensive research, resulting in a large number of important contributions. The authors of this book, together with Bent Bruun Kristensen, have been involved in the BETA project since 1975, the aim of which is to develop con- cepts, constructs and tools for programming. -
Cmsc 132: Object-Oriented Programming Ii
© Department of Computer Science UMD CMSC 132: OBJECT-ORIENTED PROGRAMMING II Iterator, Marker, Observer Design Patterns Department of Computer Science University of Maryland, College Park © Department of Computer Science UMD Design Patterns • Descriptions of reusable solutions to common software design problems (e.g, Iterator pattern) • Captures the experience of experts • Goals • Solve common programming challenges • Improve reliability of solution • Aid rapid software development • Useful for real-world applications • Design patterns are like recipes – generic solutions to expected situations • Design patterns are language independent • Recognizing when and where to use design patterns requires familiarity & experience • Design pattern libraries serve as a glossary of idioms for understanding common, but complex solutions • Design patterns are used throughout the Java Class Libraries © Department of Computer Science UMD Iterator Pattern • Definition • Move through collection of objects without knowing its internal representation • Where to use & benefits • Use a standard interface to represent data objects • Uses standard iterator built in each standard collection, like List • Need to distinguish variations in the traversal of an aggregate • Example • Iterator for collection • Original • Examine elements of collection directly • Using pattern • Collection provides Iterator class for examining elements in collection © Department of Computer Science UMD Iterator Example public interface Iterator<V> { bool hasNext(); V next(); void remove(); -
Iterators in C++ C 2016 All Rights Reserved
Software Design Lecture Notes Prof. Stewart Weiss Iterators in C++ c 2016 All rights reserved. Iterators in C++ 1 Introduction When a program needs to visit all of the elements of a vector named myvec starting with the rst and ending with the last, you could use an iterative loop such as the following: for ( int i = 0; i < myvec.size(); i++ ) // the visit, i.e., do something with myvec[i] This code works and is a perfectly ne solution. This same type of iterative loop can visit each character in a C++ string. But what if you need code that visits all elements of a C++ list object? Is there a way to use an iterative loop to do this? To be clear, an iterative loop is one that has the form for var = start value; var compared to end value; update var; {do something with node at specic index} In other words, an iterative loop is a counting loop, as opposed to one that tests an arbitrary condition, like a while loop. The short answer to the question is that, in C++, without iterators, you cannot do this. Iterators make it possible to iterate through arbitrary containers. This set of notes answers the question, What is an iterator, and how do you use it? Iterators are a generalization of pointers in C++ and have similar semantics. They allow a program to navigate through dierent types of containers in a uniform manner. Just as pointers can be used to traverse a linked list or a binary tree, and subscripts can be used to traverse the elements of a vector, iterators can be used to sequence through the elements of any standard C++ container class. -
CPS323 Lecture: Concurrency Materials: 1. Coroutine Projectables
CPS323 Lecture: Concurrency Materials: 1. Coroutine Projectables 2. Handout for Ada Concurrency + Executable form (simple_tasking.adb, producer_and_consumer.adb) I. Introduction - ------------ A. Most of our attention throughout the CS curricum has been focussed on _sequential_ programming, in which a program does exactly one thing at a time, following a predictable order of steps. In particular, we expect a given program will always follow the exact same sequence of steps when run on a given set of data. B. An alternative is to think in terms of _concurrent_ programming, in which a "program" (at least in principle) does multiple things at the same time, following an order of steps that is not predictable and may differ between runs even if the same program is run on exactly the same data. C. Concurrency has long been an interest in CS, but has become of particular interest as we move into a situation in which raw hardware speeds have basically plateaued and multicore processors are coming to dominate the hardware scene. There are at least three reasons why this topic is of great interest. 1. Achieving maximum performance using technologies such as multicore processors. 2. Systems that inherently require multiple processors working together cooperatively on a single task - e.g. distributed or embedded systems. 3. Some problems are more naturally addressed by thinking in terms of multiple concurrrent components, rather than a single monolithic program. D. There are two broad approaches that might be taken to concurrency: 1. Make use of system libraries, without directly supporting parallelism in the language. (The approach taken by most languages - e.g. -
Generic Programming
Generic Programming July 21, 1998 A Dagstuhl Seminar on the topic of Generic Programming was held April 27– May 1, 1998, with forty seven participants from ten countries. During the meeting there were thirty seven lectures, a panel session, and several problem sessions. The outcomes of the meeting include • A collection of abstracts of the lectures, made publicly available via this booklet and a web site at http://www-ca.informatik.uni-tuebingen.de/dagstuhl/gpdag.html. • Plans for a proceedings volume of papers submitted after the seminar that present (possibly extended) discussions of the topics covered in the lectures, problem sessions, and the panel session. • A list of generic programming projects and open problems, which will be maintained publicly on the World Wide Web at http://www-ca.informatik.uni-tuebingen.de/people/musser/gp/pop/index.html http://www.cs.rpi.edu/˜musser/gp/pop/index.html. 1 Contents 1 Motivation 3 2 Standards Panel 4 3 Lectures 4 3.1 Foundations and Methodology Comparisons ........ 4 Fundamentals of Generic Programming.................. 4 Jim Dehnert and Alex Stepanov Automatic Program Specialization by Partial Evaluation........ 4 Robert Gl¨uck Evaluating Generic Programming in Practice............... 6 Mehdi Jazayeri Polytypic Programming........................... 6 Johan Jeuring Recasting Algorithms As Objects: AnAlternativetoIterators . 7 Murali Sitaraman Using Genericity to Improve OO Designs................. 8 Karsten Weihe Inheritance, Genericity, and Class Hierarchies.............. 8 Wolf Zimmermann 3.2 Programming Methodology ................... 9 Hierarchical Iterators and Algorithms................... 9 Matt Austern Generic Programming in C++: Matrix Case Study........... 9 Krzysztof Czarnecki Generative Programming: Beyond Generic Programming........ 10 Ulrich Eisenecker Generic Programming Using Adaptive and Aspect-Oriented Programming . -
Generators & Coroutines Part 1: Iterators
Generators & Coroutines Part 1: Iterators Edited Version of Slides by David Beazely http://www.dabeaz.comPart I Introduction to Iterators and Generators Monday, May 16, 2011 Monday, May 16, 2011 Copyright (C) 2008, http://www.dabeaz.com 1- 11 Iteration Iterating over a Dict As you know, Python has a "for" statement • • If you loop over a dictionary you get keys You use it to loop over a collection of items • >>> prices = { 'GOOG' : 490.10, >>> for x in [1,4,5,10]: ... 'AAPL' : 145.23, ... print x, ... 'YHOO' : 21.71 } ... ... 1 4 5 10 >>> for key in prices: >>> ... print key ... And, as you have probably noticed, you can YHOO • GOOG iterate over many different kinds of objects AAPL (not just lists) >>> Copyright (C) 2008, http://www.dabeaz.com 1- 12 Copyright (C) 2008, http://www.dabeaz.com 1- 13 Iterating over a String • If you loop over a string, you get characters >>> s = "Yow!" >>> for c in s: ... print c ... Y o w ! >>> Copyright (C) 2008, http://www.dabeaz.com 1- 14 Iterating over a Dict • If you loop over a dictionary you get keys >>> prices = { 'GOOG' : 490.10, ... 'AAPL' : 145.23, ... 'YHOO' : 21.71 } ... >>> for key in prices: ... print key ... YHOO GOOG AAPL >>> Copyright (C) 2008, http://www.dabeaz.com 1- 13 Iterating over a String Iterating over a File • If you loop over a file you get lines If you loop over a string, you get characters >>> for line in open("real.txt"): • ... print line, ... >>> s = "Yow!" Iterating over a File Real Programmers write in FORTRAN >>> for c in s: .. -
An Overview of the Scala Programming Language
An Overview of the Scala Programming Language Second Edition Martin Odersky, Philippe Altherr, Vincent Cremet, Iulian Dragos Gilles Dubochet, Burak Emir, Sean McDirmid, Stéphane Micheloud, Nikolay Mihaylov, Michel Schinz, Erik Stenman, Lex Spoon, Matthias Zenger École Polytechnique Fédérale de Lausanne (EPFL) 1015 Lausanne, Switzerland Technical Report LAMP-REPORT-2006-001 Abstract guage for component software needs to be scalable in the sense that the same concepts can describe small as well as Scala fuses object-oriented and functional programming in large parts. Therefore, we concentrate on mechanisms for a statically typed programming language. It is aimed at the abstraction, composition, and decomposition rather than construction of components and component systems. This adding a large set of primitives which might be useful for paper gives an overview of the Scala language for readers components at some level of scale, but not at other lev- who are familar with programming methods and program- els. Second, we postulate that scalable support for compo- ming language design. nents can be provided by a programming language which unies and generalizes object-oriented and functional pro- gramming. For statically typed languages, of which Scala 1 Introduction is an instance, these two paradigms were up to now largely separate. True component systems have been an elusive goal of the To validate our hypotheses, Scala needs to be applied software industry. Ideally, software should be assembled in the design of components and component systems. Only from libraries of pre-written components, just as hardware is serious application by a user community can tell whether the assembled from pre-fabricated chips. -
Cmsc 132: Object-Oriented Programming Ii
© Department of Computer Science UMD CMSC 132: OBJECT-ORIENTED PROGRAMMING II Object-Oriented Programming Intro Department of Computer Science University of Maryland, College Park © Department of Computer Science UMD Object-Oriented Programming (OOP) • Approach to improving software • View software as a collection of objects (entities) • OOP takes advantage of two techniques • Abstraction • Encapsulation © Department of Computer Science UMD Techniques – Abstraction • Abstraction • Provide high-level model of activity or data • Don’t worry about the details. What does it do, not how • Example from outside of CS: Microwave Oven • Procedural abstraction • Specify what actions should be performed • Hide algorithms • Example: Sort numbers in an array (is it Bubble sort? Quicksort? etc.) • Data abstraction • Specify data objects for problem • Hide representation • Example: List of names • Abstract Data Type (ADT) • Implementation independent of interfaces • Example: The ADT is a map (also called a dictionary). We know it should associate a key with a value. Can be implemented in different ways: binary search tree, hash table, or a list. © Department of Computer Science UMD Techniques – Encapsulation • Encapsulation • Definition: A design technique that calls for hiding implementation details while providing an interface (methods) for data access • Example: use the keyword private when designing Java classes • Allow us to use code without having to know its implementation (supports the concept of abstraction) • Simplifies the process of code -
A Low-Cost Implementation of Coroutines for C
University of Wollongong Research Online Department of Computing Science Working Faculty of Engineering and Information Paper Series Sciences 1983 A low-cost implementation of coroutines for C Paul A. Bailes University of Wollongong Follow this and additional works at: https://ro.uow.edu.au/compsciwp Recommended Citation Bailes, Paul A., A low-cost implementation of coroutines for C, Department of Computing Science, University of Wollongong, Working Paper 83-9, 1983, 24p. https://ro.uow.edu.au/compsciwp/76 Research Online is the open access institutional repository for the University of Wollongong. For further information contact the UOW Library: [email protected] A LOW-COST IMPLEMENTATION OF COROUTINES FOR C Paul A. Bailes Department of Computing Science University of Wollongong Preprint No. 83-9 November 16, 1983 P.O. Box 1144, WOLLONGONG N.S.W. 2500, AUSTRALIA tel (042)-282-981 telex AA29022 A Low-Cost Implementation of Coroutines for C Paul A. Bailes Department of Computing Science University of Wollongong Wollongong N.S.W. 2500 Australia ABSTRACT We identify a set of primitive operations supporting coroutines, and demonstrate their usefulness. We then address their implementation in C accord ing to a set of criteria aimed at maintaining simplicity, and achieve a satisfactory compromise between it and effectiveness. Our package for the PDP-II under UNIXt allows users of coroutines in C programs to gain access to the primitives via an included definitions file and an object library; no penalty is imposed upon non-coroutine users. October 6, 1983 tUNIX is a Trademark of Bell Laboratories. A Low-Cost Implementation of Coroutines for C Paul A.