A Domain-Specific Interpreter for Parallelizing a Large Mixed
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Ironpython in Action
IronPytho IN ACTION Michael J. Foord Christian Muirhead FOREWORD BY JIM HUGUNIN MANNING IronPython in Action Download at Boykma.Com Licensed to Deborah Christiansen <[email protected]> Download at Boykma.Com Licensed to Deborah Christiansen <[email protected]> IronPython in Action MICHAEL J. FOORD CHRISTIAN MUIRHEAD MANNING Greenwich (74° w. long.) Download at Boykma.Com Licensed to Deborah Christiansen <[email protected]> For online information and ordering of this and other Manning books, please visit www.manning.com. The publisher offers discounts on this book when ordered in quantity. For more information, please contact Special Sales Department Manning Publications Co. Sound View Court 3B fax: (609) 877-8256 Greenwich, CT 06830 email: [email protected] ©2009 by Manning Publications Co. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by means electronic, mechanical, photocopying, or otherwise, without prior written permission of the publisher. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in the book, and Manning Publications was aware of a trademark claim, the designations have been printed in initial caps or all caps. Recognizing the importance of preserving what has been written, it is Manning’s policy to have the books we publish printed on acid-free paper, and we exert our best efforts to that end. Recognizing also our responsibility to conserve the resources of our planet, Manning books are printed on paper that is at least 15% recycled and processed without the use of elemental chlorine. -
Ece351 Lab Manual
DEREK RAYSIDE & ECE351 STAFF ECE351 LAB MANUAL UNIVERSITYOFWATERLOO 2 derek rayside & ece351 staff Copyright © 2014 Derek Rayside & ECE351 Staff Compiled March 6, 2014 acknowledgements: • Prof Paul Ward suggested that we look into something with vhdl to have synergy with ece327. • Prof Mark Aagaard, as the ece327 instructor, consulted throughout the development of this material. • Prof Patrick Lam generously shared his material from the last offering of ece251. • Zhengfang (Alex) Duanmu & Lingyun (Luke) Li [1b Elec] wrote solutions to most labs in txl. • Jiantong (David) Gao & Rui (Ray) Kong [3b Comp] wrote solutions to the vhdl labs in antlr. • Aman Muthrej and Atulan Zaman [3a Comp] wrote solutions to the vhdl labs in Parboiled. • TA’s Jon Eyolfson, Vajih Montaghami, Alireza Mortezaei, Wenzhu Man, and Mohammed Hassan. • TA Wallace Wu developed the vhdl labs. • High school students Brian Engio and Tianyu Guo drew a number of diagrams for this manual, wrote Javadoc comments for the code, and provided helpful comments on the manual. Licensed under Creative Commons Attribution-ShareAlike (CC BY-SA) version 2.5 or greater. http://creativecommons.org/licenses/by-sa/2.5/ca/ http://creativecommons.org/licenses/by-sa/3.0/ Contents 0 Overview 9 Compiler Concepts: call stack, heap 0.1 How the Labs Fit Together . 9 Programming Concepts: version control, push, pull, merge, SSH keys, IDE, 0.2 Learning Progressions . 11 debugger, objects, pointers 0.3 How this project compares to CS241, the text book, etc. 13 0.4 Student work load . 14 0.5 How this course compares to MIT 6.035 .......... 15 0.6 Where do I learn more? . -
Design Pattern Interview Questions
DDEESSIIGGNN PPAATTTTEERRNN -- IINNTTEERRVVIIEEWW QQUUEESSTTIIOONNSS http://www.tutorialspoint.com/design_pattern/design_pattern_interview_questions.htm Copyright © tutorialspoint.com Dear readers, these Design Pattern Interview Questions have been designed specially to get you acquainted with the nature of questions you may encounter during your interview for the subject of Design Pattern. As per my experience good interviewers hardly plan to ask any particular question during your interview, normally questions start with some basic concept of the subject and later they continue based on further discussion and what you answer: What are Design Patterns? Design patterns represent the best practices used by experienced object-oriented software developers. Design patterns are solutions to general problems that software developers faced during software development. These solutions were obtained by trial and error by numerous software developers over quite a substantial period of time. What is Gang of Four GOF? In 1994, four authors Erich Gamma, Richard Helm, Ralph Johnson and John Vlissides published a book titled Design Patterns - Elements of Reusable Object-Oriented Software which initiated the concept of Design Pattern in Software development. These authors are collectively known as Gang of Four GOF. Name types of Design Patterns? Design patterns can be classified in three categories: Creational, Structural and Behavioral patterns. Creational Patterns - These design patterns provide a way to create objects while hiding the creation logic, rather than instantiating objects directly using new opreator. This gives program more flexibility in deciding which objects need to be created for a given use case. Structural Patterns - These design patterns concern class and object composition. Concept of inheritance is used to compose interfaces and define ways to compose objects to obtain new functionalities. -
CIS 192: Lecture 12 Deploying Apps and Concurrency
CIS 192: Lecture 12 Deploying Apps and Concurrency Lili Dworkin University of Pennsylvania Good Question from Way Back I All HTTP requests have 1) URL, 2) headers, 3) body I GET requests: parameters sent in URL I POST requests: parameters sent in body Can GET requests have a body? StackOverflow's response: \Yes, you can send a request body with GET but it should not have any meaning. If you give it meaning by parsing it on the server and changing your response based on its contents you're violating the HTTP/1.1 spec." Good Question from Last Week What is the difference between jsonify and json.dumps? def jsonify(*args, **kwargs): if __debug__: _assert_have_json() return current_app.response_class(json.dumps(dict(* args, **kwargs), indent=None if request.is_xhr else 2), mimetype='application/json') I jsonify returns a Response object I jsonify automatically sets content-type header I jsonify also sets the indentation Review Find a partner! Deploying Apps I We've been running Flask apps locally on a builtin development server I When you're ready to go public, you need to deploy to a production server I Easiest option: use one hosted by someone else! I We'll use Heroku, a platform as a service (PaaS) that makes it easy to deploy apps in a variety of languages Heroku Prerequisites: I Virtualenv (creates standalone Python environments) I Heroku toolbox I Heroku command-line client I Git (for version control and pushing to Heroku) Virtualenv I Allows us to create a virtual Python environment I Unique, isolated environment for each project I Use case: different versions of packages for different projects Virtualenv How to use it? prompt$ pip install virtualenv Now navigate to your project directory: prompt$ virtualenv --no-site-packages venv prompt$ source venv/bin/activate (<name>)prompt$ pip install Flask gunicorn (<name>)prompt$ deactivate prompt% Heroku Toolbox Once you make a Heroku account, install the Heroku toolbox. -
Behavioral Patterns
Behavioral Patterns 101 What are Behavioral Patterns ! " Describe algorithms, assignment of responsibility, and interactions between objects (behavioral relationships) ! " Behavioral class patterns use inheritence to distribute behavior ! " Behavioral object patterns use composition ! " General example: ! " Model-view-controller in UI application ! " Iterating over a collection of objects ! " Comparable interface in Java !" 2003 - 2007 DevelopIntelligence List of Structural Patterns ! " Class scope pattern: ! " Interpreter ! " Template Method ! " Object scope patterns: ! " Chain of Responsibility ! " Command ! " Iterator ! " Mediator ! " Memento ! " Observer ! " State ! " Strategy ! " Visitor !" 2003 - 2007 DevelopIntelligence CoR Pattern Description ! " Intent: Avoid coupling the sender of a request to its receiver by giving more than one object a chance to handle the request. Chain the receiving objects and pass the request along the chain until an object handles it. ! " AKA: Handle/Body ! " Motivation: User Interfaces function as a result of user interactions, known as events. Events can be handled by a component, a container, or the operating system. In the end, the event handling should be decoupled from the component. ! " Applicability: ! " more than one object may handle a request, and the handler isn't known a priori. ! " Want to issue a request to one of several objects without specifying the receiver !" 2003 - 2007 DevelopIntelligence CoR Real World Example ! " The Chain of Responsibility pattern avoids coupling the sender of a request to the receiver, by giving more than one object a chance to handle the request. ! " Mechanical coin sorting banks use the Chain of Responsibility. Rather than having a separate slot for each coin denomination coupled with receptacle for the denomination, a single slot is used. When the coin is dropped, the coin is routed to the appropriate receptacle by the mechanical mechanisms within the bank. -
Design Patterns (Part 3)
Design patterns (part 3) CSE 331 University of Washington Michael Ernst Outline Introduction to design patterns Creational patterns (constructing objects) Structural patterns (controlling heap layout) ⇒Behavioral patterns (affecting object semantics) Composite pattern Composite permits a client to manipulate either an atomic unit or a collection of units in the same way Good for dealing with part-whole relationships Composite example: Bicycle • Bicycle – Wheel • Skewer • Hub • Spokes • Nipples • Rim • Tape • Tube • Tire – Frame – Drivetrain – ... Methods on components class BicycleComponent { int weight (); float cost (); } class Skewer extends BicycleComponent { float price ; float cost () { return price; } } class Wheel extends BicycleComponent { float assemblyCost ; Skewer skewer ; Hub hub ; ... float cost () { return assemblyCost + skewer.cost() + hub.cost() + ...; } } Composite example: Libraries Library Section (for a given genre) Shelf Volume Page Column Word Letter interface Text { String getText (); } class Page implements Text { String getText () { ... return the concatenation of the column texts ... } } Traversing composites Goal: perform operations on all parts of a composite Representing Java code x = foo * b + c / d; = x + * / foo b c d Abstract syntax tree (AST) for Java code class PlusOp extends Expression { // + operation Expression leftExp ; Expression rightExp ; } class VarRef extends Expression { // variable reference String varname ; } class EqualOp extends Expression { // equality test a==b; Expression lvalue ; // -
Automatic Generation of Truffle-Based Interpreters for Domain
Automatic generation of Truffle-based interpreters for Domain-Specific Languages Manuel Leduc, Gwendal Jouneaux, Thomas Degueule, Gurvan Le Guernic, Olivier Barais, Benoit Combemale To cite this version: Manuel Leduc, Gwendal Jouneaux, Thomas Degueule, Gurvan Le Guernic, Olivier Barais, et al.. Automatic generation of Truffle-based interpreters for Domain-Specific Languages. The Journal of Object Technology, Chair of Software Engineering, 2020, 19 (2), pp.1-21. 10.5381/jot.2020.19.2.a1. hal-02395867v2 HAL Id: hal-02395867 https://hal.inria.fr/hal-02395867v2 Submitted on 21 Feb 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Journal of Object Technology Published by AITO — Association Internationale pour les Technologies Objets http://www.jot.fm/ Automatic generation of Truffle-based interpreters for Domain-Specific Languages Manuel Leduca Gwendal Jouneauxa Thomas Degueuleb Gurvan Le Guernicc Olivier Baraisa Benoit Combemalead a. Univ. Rennes, Inria, CNRS, IRISA, France b. Univ. Bordeaux, Bordeaux INP, CNRS, LaBRI, UMR5800, F-33400 Talence, France c. DGA MI, Bruz, France d. Univ. Toulouse, IRIT, France Abstract Numerous language workbenches have been proposed over the past decade to ease the definition of Domain-Specific Languages (DSLs). -
Threading and GUI Issues for R
Threading and GUI Issues for R Luke Tierney School of Statistics University of Minnesota March 5, 2001 Contents 1 Introduction 2 2 Concurrency and Parallelism 2 3 Concurrency and Dynamic State 3 3.1 Options Settings . 3 3.2 User Defined Options . 5 3.3 Devices and Par Settings . 5 3.4 Standard Connections . 6 3.5 The Context Stack . 6 3.5.1 Synchronization . 6 4 GUI Events And Blocking IO 6 4.1 UNIX Issues . 7 4.2 Win32 Issues . 7 4.3 Classic MacOS Issues . 8 4.4 Implementations To Consider . 8 4.5 A Note On Java . 8 4.6 A Strategy for GUI/IO Management . 9 4.7 A Sample Implementation . 9 5 Threads and GUI’s 10 6 Threading Design Space 11 6.1 Parallelism Through HL Threads: The MXM Options . 12 6.2 Light-Weight Threads: The XMX Options . 12 6.3 Multiple OS Threads Running One At A Time: MSS . 14 6.4 Variations on OS Threads . 14 6.5 SMS or MXS: Which To Choose? . 14 7 Light-Weight Thread Implementation 14 1 March 5, 2001 2 8 Other Issues 15 8.1 High-Level GUI Interfaces . 16 8.2 High-Level Thread Interfaces . 16 8.3 High-Level Streams Interfaces . 16 8.4 Completely Random Stuff . 16 1 Introduction This document collects some random thoughts on runtime issues relating to concurrency, threads, GUI’s and the like. Some of this is extracted from recent R-core email threads. I’ve tried to provide lots of references that might be of use. -
Due to Global Interpreter Lock (GIL), Python Threads Do Not Provide Efficient Multi-Core Execution, Unlike Other Languages Such As Golang
Due to global interpreter lock (GIL), python threads do not provide efficient multi-core execution, unlike other languages such as golang. Asynchronous programming in python is focusing on single core execution. Happily, Nexedi python code base already supports high performance multi-core execution either through multiprocessing with distributed shared memory or by relying on components (NumPy, MariaDB) that already support multiple core execution. The impatient reader will find bellow a table that summarises current options to achieve high performance multi-core performance in python. High Performance multi-core Python Cheat Sheet Use python whenever you can rely on any of... Use golang whenever you need at the same time... low latency multiprocessing high concurrency cython's nogil option multi-core execution within single userspace shared multi-core execution within wendelin.core distributed memory shared memory something else than cython's parallel module or cython's parallel module nogil option Here are a set of rules to achieve high performance on a multi-core system in the context of Nexedi stack. use ERP5's CMFActivity by default, since it can solve 99% of your concurrency and performance problems on a cluster or multi-core system; use parallel module in cython if you need to use all cores with high performance within a single transaction (ex. HTTP request); use threads in python together with nogil option in cython in order to use all cores on a multithreaded python process (ex. Zope); use cython to achieve C/C++ performance without mastering C/C++ as long as you do not need multi-core asynchronous programming; rewrite some python in cython to get performance boost on selected portions of python libraries; use numba to accelerate selection portions of python code with JIT that may also work in a dynamic context (ex. -
Java Design Patterns I
Java Design Patterns i Java Design Patterns Java Design Patterns ii Contents 1 Introduction to Design Patterns 1 1.1 Introduction......................................................1 1.2 What are Design Patterns...............................................1 1.3 Why use them.....................................................2 1.4 How to select and use one...............................................2 1.5 Categorization of patterns...............................................3 1.5.1 Creational patterns..............................................3 1.5.2 Structural patterns..............................................3 1.5.3 Behavior patterns...............................................3 2 Adapter Design Pattern 5 2.1 Adapter Pattern....................................................5 2.2 An Adapter to rescue.................................................6 2.3 Solution to the problem................................................7 2.4 Class Adapter..................................................... 11 2.5 When to use Adapter Pattern............................................. 12 2.6 Download the Source Code.............................................. 12 3 Facade Design Pattern 13 3.1 Introduction...................................................... 13 3.2 What is the Facade Pattern.............................................. 13 3.3 Solution to the problem................................................ 14 3.4 Use of the Facade Pattern............................................... 16 3.5 Download the Source Code............................................. -
Table of Contents
Table of Contents ± -—T^jTp^om Object-Oriented to Functional Programming 5 Chajava- an introduction 5 java programming paradigms 6 CO imperative programming CD Real-life imperative example Object-oriented paradigm 7 Objects and classes 7 Encapsulation 7 Abstraction 8 Inheritance 8 Polymorphism 9 Declarative programming 10 Functional programming 11 Working with collections versus working with streams 11 An introduction to Unified Modeling Language 12 Class relations 14 Generalization 15 Realization 15 Dependency 16 Association 16 Aggregation 16 Composition 17 Design patterns and principles 17 Single responsibility principle 18 Open/closed principle 20 Liskov Substitution Principle 20 Interface Segregation Principle 22 Dependency inversion principle 23 Summary 24 Chapter 2: Creational Patterns 27 Singleton pattern 27 Synchronized singletons 29 Synchronized singleton with double-checked locking mechanism 30 Lock-free thread-safe singleton 30 tu * y and lazy loacling 31 i he factory pattern 31 Simple factory pattern 32 Table of Contents Static factory 33 Simple factory with class registration using reflection 34 Simple factory with class registration using Product.newlnstance 35 Factory method pattern 36 Anonymous concrete factory 38 Abstract factory 38 Simple factory versus factory method versus abstract factory 40 Builder pattern 40 Car builder example 41 Simplified builder pattern 43 Anonymous builders with method chaining 44 Prototype pattern 45 Shallow clone versus deep clone Object pool pattern Summary аэоэсБ Chapter 3: Behavioral Patterns -
Specialising Dynamic Techniques for Implementing the Ruby Programming Language
SPECIALISING DYNAMIC TECHNIQUES FOR IMPLEMENTING THE RUBY PROGRAMMING LANGUAGE A thesis submitted to the University of Manchester for the degree of Doctor of Philosophy in the Faculty of Engineering and Physical Sciences 2015 By Chris Seaton School of Computer Science This published copy of the thesis contains a couple of minor typographical corrections from the version deposited in the University of Manchester Library. [email protected] chrisseaton.com/phd 2 Contents List of Listings7 List of Tables9 List of Figures 11 Abstract 15 Declaration 17 Copyright 19 Acknowledgements 21 1 Introduction 23 1.1 Dynamic Programming Languages.................. 23 1.2 Idiomatic Ruby............................ 25 1.3 Research Questions.......................... 27 1.4 Implementation Work......................... 27 1.5 Contributions............................. 28 1.6 Publications.............................. 29 1.7 Thesis Structure............................ 31 2 Characteristics of Dynamic Languages 35 2.1 Ruby.................................. 35 2.2 Ruby on Rails............................. 36 2.3 Case Study: Idiomatic Ruby..................... 37 2.4 Summary............................... 49 3 3 Implementation of Dynamic Languages 51 3.1 Foundational Techniques....................... 51 3.2 Applied Techniques.......................... 59 3.3 Implementations of Ruby....................... 65 3.4 Parallelism and Concurrency..................... 72 3.5 Summary............................... 73 4 Evaluation Methodology 75 4.1 Evaluation Philosophy