Memory Management and Garbage Collection
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Project Snowflake: Non-Blocking Safe Manual Memory Management in .NET
Project Snowflake: Non-blocking Safe Manual Memory Management in .NET Matthew Parkinson Dimitrios Vytiniotis Kapil Vaswani Manuel Costa Pantazis Deligiannis Microsoft Research Dylan McDermott Aaron Blankstein Jonathan Balkind University of Cambridge Princeton University July 26, 2017 Abstract Garbage collection greatly improves programmer productivity and ensures memory safety. Manual memory management on the other hand often delivers better performance but is typically unsafe and can lead to system crashes or security vulnerabilities. We propose integrating safe manual memory management with garbage collection in the .NET runtime to get the best of both worlds. In our design, programmers can choose between allocating objects in the garbage collected heap or the manual heap. All existing applications run unmodified, and without any performance degradation, using the garbage collected heap. Our programming model for manual memory management is flexible: although objects in the manual heap can have a single owning pointer, we allow deallocation at any program point and concurrent sharing of these objects amongst all the threads in the program. Experimental results from our .NET CoreCLR implementation on real-world applications show substantial performance gains especially in multithreaded scenarios: up to 3x savings in peak working sets and 2x improvements in runtime. 1 Introduction The importance of garbage collection (GC) in modern software cannot be overstated. GC greatly improves programmer productivity because it frees programmers from the burden of thinking about object lifetimes and freeing memory. Even more importantly, GC prevents temporal memory safety errors, i.e., uses of memory after it has been freed, which often lead to security breaches. Modern generational collectors, such as the .NET GC, deliver great throughput through a combination of fast thread-local bump allocation and cheap collection of young objects [63, 18, 61]. -
Memory Management with Explicit Regions by David Edward Gay
Memory Management with Explicit Regions by David Edward Gay Engineering Diploma (Ecole Polytechnique F´ed´erale de Lausanne, Switzerland) 1992 M.S. (University of California, Berkeley) 1997 A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Computer Science in the GRADUATE DIVISION of the UNIVERSITY of CALIFORNIA at BERKELEY Committee in charge: Professor Alex Aiken, Chair Professor Susan L. Graham Professor Gregory L. Fenves Fall 2001 The dissertation of David Edward Gay is approved: Chair Date Date Date University of California at Berkeley Fall 2001 Memory Management with Explicit Regions Copyright 2001 by David Edward Gay 1 Abstract Memory Management with Explicit Regions by David Edward Gay Doctor of Philosophy in Computer Science University of California at Berkeley Professor Alex Aiken, Chair Region-based memory management systems structure memory by grouping objects in regions under program control. Memory is reclaimed by deleting regions, freeing all objects stored therein. Our compiler for C with regions, RC, prevents unsafe region deletions by keeping a count of references to each region. RC's regions have advantages over explicit allocation and deallocation (safety) and traditional garbage collection (better control over memory), and its performance is competitive with both|from 6% slower to 55% faster on a collection of realistic benchmarks. Experience with these benchmarks suggests that modifying many existing programs to use regions is not difficult. An important innovation in RC is the use of type annotations that make the structure of a program's regions more explicit. These annotations also help reduce the overhead of reference counting from a maximum of 25% to a maximum of 12.6% on our benchmarks. -
Transparent Garbage Collection for C++
Document Number: WG21/N1833=05-0093 Date: 2005-06-24 Reply to: Hans-J. Boehm [email protected] 1501 Page Mill Rd., MS 1138 Palo Alto CA 94304 USA Transparent Garbage Collection for C++ Hans Boehm Michael Spertus Abstract A number of possible approaches to automatic memory management in C++ have been considered over the years. Here we propose the re- consideration of an approach that relies on partially conservative garbage collection. Its principal advantage is that objects referenced by ordinary pointers may be garbage-collected. Unlike other approaches, this makes it possible to garbage-collect ob- jects allocated and manipulated by most legacy libraries. This makes it much easier to convert existing code to a garbage-collected environment. It also means that it can be used, for example, to “repair” legacy code with deficient memory management. The approach taken here is similar to that taken by Bjarne Strous- trup’s much earlier proposal (N0932=96-0114). Based on prior discussion on the core reflector, this version does insist that implementations make an attempt at garbage collection if so requested by the application. How- ever, since there is no real notion of space usage in the standard, there is no way to make this a substantive requirement. An implementation that “garbage collects” by deallocating all collectable memory at process exit will remain conforming, though it is likely to be unsatisfactory for some uses. 1 Introduction A number of different mechanisms for adding automatic memory reclamation (garbage collection) to C++ have been considered: 1. Smart-pointer-based approaches which recycle objects no longer ref- erenced via special library-defined replacement pointer types. -
Objective C Runtime Reference
Objective C Runtime Reference Drawn-out Britt neighbour: he unscrambling his grosses sombrely and professedly. Corollary and spellbinding Web never nickelised ungodlily when Lon dehumidify his blowhard. Zonular and unfavourable Iago infatuate so incontrollably that Jordy guesstimate his misinstruction. Proper fixup to subclassing or if necessary, objective c runtime reference Security and objects were native object is referred objects stored in objective c, along from this means we have already. Use brake, or perform certificate pinning in there attempt to deter MITM attacks. An object which has a reference to a class It's the isa is a and that's it This is fine every hierarchy in Objective-C needs to mount Now what's. Use direct access control the man page. This function allows us to voluntary a reference on every self object. The exception handling code uses a header file implementing the generic parts of the Itanium EH ABI. If the method is almost in the cache, thanks to Medium Members. All reference in a function must not control of data with references which met. Understanding the Objective-C Runtime Logo Table Of Contents. Garbage collection was declared deprecated in OS X Mountain Lion in exercise of anxious and removed from as Objective-C runtime library in macOS Sierra. Objective-C Runtime Reference. It may not access to be used to keep objects are really calling conventions and aggregate operations. Thank has for putting so in effort than your posts. This will cut down on the alien of Objective C runtime information. Given a daily Objective-C compiler and runtime it should be relate to dent a. -
Lecture 15 Garbage Collection I
Lecture 15 Garbage Collection I. Introduction to GC -- Reference Counting -- Basic Trace-Based GC II. Copying Collectors III. Break Up GC in Time (Incremental) IV. Break Up GC in Space (Partial) Readings: Ch. 7.4 - 7.7.4 Carnegie Mellon M. Lam CS243: Advanced Garbage Collection 1 I. Why Automatic Memory Management? • Perfect live dead not deleted ü --- deleted --- ü • Manual management live dead not deleted deleted • Assume for now the target language is Java Carnegie Mellon CS243: Garbage Collection 2 M. Lam What is Garbage? Carnegie Mellon CS243: Garbage Collection 3 M. Lam When is an Object not Reachable? • Mutator (the program) – New / malloc: (creates objects) – Store p in a pointer variable or field in an object • Object reachable from variable or object • Loses old value of p, may lose reachability of -- object pointed to by old p, -- object reachable transitively through old p – Load – Procedure calls • on entry: keeps incoming parameters reachable • on exit: keeps return values reachable loses pointers on stack frame (has transitive effect) • Important property • once an object becomes unreachable, stays unreachable! Carnegie Mellon CS243: Garbage Collection 4 M. Lam How to Find Unreachable Nodes? Carnegie Mellon CS243: Garbage Collection 5 M. Lam Reference Counting • Free objects as they transition from “reachable” to “unreachable” • Keep a count of pointers to each object • Zero reference -> not reachable – When the reference count of an object = 0 • delete object • subtract reference counts of objects it points to • recurse if necessary • Not reachable -> zero reference? • Cost – overhead for each statement that changes ref. counts Carnegie Mellon CS243: Garbage Collection 6 M. -
Linear Algebra Libraries
Linear Algebra Libraries Claire Mouton [email protected] March 2009 Contents I Requirements 3 II CPPLapack 4 III Eigen 5 IV Flens 7 V Gmm++ 9 VI GNU Scientific Library (GSL) 11 VII IT++ 12 VIII Lapack++ 13 arXiv:1103.3020v1 [cs.MS] 15 Mar 2011 IX Matrix Template Library (MTL) 14 X PETSc 16 XI Seldon 17 XII SparseLib++ 18 XIII Template Numerical Toolkit (TNT) 19 XIV Trilinos 20 1 XV uBlas 22 XVI Other Libraries 23 XVII Links and Benchmarks 25 1 Links 25 2 Benchmarks 25 2.1 Benchmarks for Linear Algebra Libraries . ....... 25 2.2 BenchmarksincludingSeldon . 26 2.2.1 BenchmarksforDenseMatrix. 26 2.2.2 BenchmarksforSparseMatrix . 29 XVIII Appendix 30 3 Flens Overloaded Operator Performance Compared to Seldon 30 4 Flens, Seldon and Trilinos Content Comparisons 32 4.1 Available Matrix Types from Blas (Flens and Seldon) . ........ 32 4.2 Available Interfaces to Blas and Lapack Routines (Flens and Seldon) . 33 4.3 Available Interfaces to Blas and Lapack Routines (Trilinos) ......... 40 5 Flens and Seldon Synoptic Comparison 41 2 Part I Requirements This document has been written to help in the choice of a linear algebra library to be included in Verdandi, a scientific library for data assimilation. The main requirements are 1. Portability: Verdandi should compile on BSD systems, Linux, MacOS, Unix and Windows. Beyond the portability itself, this often ensures that most compilers will accept Verdandi. An obvious consequence is that all dependencies of Verdandi must be portable, especially the linear algebra library. 2. High-level interface: the dependencies should be compatible with the building of the high-level interface (e. -
Memory Management
Memory management The memory of a computer is a finite resource. Typical Memory programs use a lot of memory over their lifetime, but not all of it at the same time. The aim of memory management is to use that finite management resource as efficiently as possible, according to some criterion. Advanced Compiler Construction In general, programs dynamically allocate memory from two different areas: the stack and the heap. Since the Michel Schinz — 2014–04–10 management of the stack is trivial, the term memory management usually designates that of the heap. 1 2 The memory manager Explicit deallocation The memory manager is the part of the run time system in Explicit memory deallocation presents several problems: charge of managing heap memory. 1. memory can be freed too early, which leads to Its job consists in maintaining the set of free memory blocks dangling pointers — and then to data corruption, (also called objects later) and to use them to fulfill allocation crashes, security issues, etc. requests from the program. 2. memory can be freed too late — or never — which leads Memory deallocation can be either explicit or implicit: to space leaks. – it is explicit when the program asks for a block to be Due to these problems, most modern programming freed, languages are designed to provide implicit deallocation, – it is implicit when the memory manager automatically also called automatic memory management — or garbage tries to free unused blocks when it does not have collection, even though garbage collection refers to a enough free memory to satisfy an allocation request. specific kind of automatic memory management. -
Programming Language Concepts Memory Management in Different
Programming Language Concepts Memory management in different languages Janyl Jumadinova 13 April, 2017 I Use external software, such as the Boehm-Demers-Weiser collector (a.k.a. Boehm GC), to do garbage collection in C/C++: { use Boehm instead of traditional malloc and free in C http://hboehm.info/gc/ C I Memory management is typically manual: { the standard library functions for memory management in C, malloc and free, have become almost synonymous with manual memory management. 2/16 C I Memory management is typically manual: { the standard library functions for memory management in C, malloc and free, have become almost synonymous with manual memory management. I Use external software, such as the Boehm-Demers-Weiser collector (a.k.a. Boehm GC), to do garbage collection in C/C++: { use Boehm instead of traditional malloc and free in C http://hboehm.info/gc/ 2/16 I In addition to Boehm, we can use smart pointers as a memory management solution. C++ I The standard library functions for memory management in C++ are new and delete. I The higher abstraction level of C++ makes the bookkeeping required for manual memory management even harder than C. 3/16 C++ I The standard library functions for memory management in C++ are new and delete. I The higher abstraction level of C++ makes the bookkeeping required for manual memory management even harder than C. I In addition to Boehm, we can use smart pointers as a memory management solution. 3/16 Smart pointer: // declare a smart pointer on stack // and pass it the raw pointer SomeSmartPtr<MyObject> ptr(new MyObject()); ptr->DoSomething(); // use the object in some way // destruction of the object happens automatically C++ Raw pointer: MyClass *ptr = new MyClass(); ptr->doSomething(); delete ptr; // destroy the object. -
Memory Management Algorithms and Implementation in C/C++
Memory Management Algorithms and Implementation in C/C++ by Bill Blunden Wordware Publishing, Inc. Library of Congress Cataloging-in-Publication Data Blunden, Bill, 1969- Memory management: algorithms and implementation in C/C++ / by Bill Blunden. p. cm. Includes bibliographical references and index. ISBN 1-55622-347-1 1. Memory management (Computer science) 2. Computer algorithms. 3. C (Computer program language) 4. C++ (Computer program language) I. Title. QA76.9.M45 .B558 2002 005.4'35--dc21 2002012447 CIP © 2003, Wordware Publishing, Inc. All Rights Reserved 2320 Los Rios Boulevard Plano, Texas 75074 No part of this book may be reproduced in any form or by any means without permission in writing from Wordware Publishing, Inc. Printed in the United States of America ISBN 1-55622-347-1 10987654321 0208 Product names mentioned are used for identification purposes only and may be trademarks of their respective companies. All inquiries for volume purchases of this book should be addressed to Wordware Publishing, Inc., at the above address. Telephone inquiries may be made by calling: (972) 423-0090 This book is dedicated to Rob, Julie, and Theo. And also to David M. Lee “I came to learn physics, and I got Jimmy Stewart” iii Table of Contents Acknowledgments......................xi Introduction.........................xiii Chapter 1 Memory Management Mechanisms. 1 MechanismVersusPolicy..................1 MemoryHierarchy......................3 AddressLinesandBuses...................9 Intel Pentium Architecture . 11 RealModeOperation...................14 Protected Mode Operation. 18 Protected Mode Segmentation . 19 ProtectedModePaging................26 PagingasProtection..................31 Addresses: Logical, Linear, and Physical . 33 PageFramesandPages................34 Case Study: Switching to Protected Mode . 35 ClosingThoughts......................42 References..........................43 Chapter 2 Memory Management Policies. -
Object Oriented Programming in Objective-C 2501ICT/7421ICT Nathan
Subclasses, Access Control, and Class Methods Advanced Topics Object Oriented Programming in Objective-C 2501ICT/7421ICT Nathan René Hexel School of Information and Communication Technology Griffith University Semester 1, 2012 René Hexel Object Oriented Programming in Objective-C Subclasses, Access Control, and Class Methods Advanced Topics Outline 1 Subclasses, Access Control, and Class Methods Subclasses and Access Control Class Methods 2 Advanced Topics Memory Management Strings René Hexel Object Oriented Programming in Objective-C Subclasses, Access Control, and Class Methods Subclasses and Access Control Advanced Topics Class Methods Objective-C Subclasses Objective-C Subclasses René Hexel Object Oriented Programming in Objective-C Subclasses, Access Control, and Class Methods Subclasses and Access Control Advanced Topics Class Methods Subclasses in Objective-C Classes can extend other classes @interface AClass: NSObject every class should extend at least NSObject, the root class to subclass a different class, replace NSObject with the class you want to extend self references the current object super references the parent class for method invocations René Hexel Object Oriented Programming in Objective-C Subclasses, Access Control, and Class Methods Subclasses and Access Control Advanced Topics Class Methods Creating Subclasses: Point3D Parent Class: Point.h Child Class: Point3D.h #import <Foundation/Foundation.h> #import "Point.h" @interface Point: NSObject @interface Point3D: Point { { int x; // member variables int z; // add z dimension -
Basic Garbage Collection Garbage Collection (GC) Is the Automatic
Basic Garbage Collection Garbage Collection (GC) is the automatic reclamation of heap records that will never again be accessed by the program. GC is universally used for languages with closures and complex data structures that are implicitly heap-allocated. GC may be useful for any language that supports heap allocation, because it obviates the need for explicit deallocation, which is tedious, error-prone, and often non- modular. GC technology is increasingly interesting for “conventional” language implementation, especially as users discover that free isn’t free. i.e., explicit memory management can be costly too. We view GC as part of an allocation service provided by the runtime environment to the user program, usually called the mutator( user program). When the mutator needs heap space, it calls an allocation routine, which in turn performs garbage collection activities if needed. Many high-level programming languages remove the burden of manual memory management from the programmer by offering automatic garbage collection, which deallocates unreachable data. Garbage collection dates back to the initial implementation of Lisp in 1958. Other significant languages that offer garbage collection include Java, Perl, ML, Modula-3, Prolog, and Smalltalk. Principles The basic principles of garbage collection are: 1. Find data objects in a program that cannot be accessed in the future 2. Reclaim the resources used by those objects Many computer languages require garbage collection, either as part of the language specification (e.g., Java, C#, and most scripting languages) or effectively for practical implementation (e.g., formal languages like lambda calculus); these are said to be garbage collected languages. -
Lecture 14 Garbage Collection I
Lecture 14 Garbage Collection I. Introduction to GC -- Reference Counting -- Basic Trace-Based GC II. Copying Collectors III. Break Up GC in Time (Incremental) IV. Break Up GC in Space (Partial) Readings: Ch. 7.4 - 7.7.4 Carnegie Mellon M. Lam CS243: Garbage Collection 1 I. What is Garbage? • Ideal: Eliminate all dead objects • In practice: Unreachable objects Carnegie Mellon CS243: Garbage Collection 2 M. Lam Two Approaches to Garbage Collection Unreachable Reachable Reachable Unreachable What is not reachable, cannot be found! Catch the transition Needs to find the complement from reachable to unreachable. of reachable objects. Reference counting Cannot collect a single object until all reachable objects are found! Stop-the-world garbage collection! Carnegie Mellon CS243: Garbage Collection 3 M. Lam When is an Object not Reachable? • Mutator (the program) – New / malloc: (creates objects) – Store: q = p; p->o1, q->o2 +: q->o1 -: If q is the only ptr to o2, o2 loses reachability If o2 holds unique pointers to any object, they lose reachability More? Applies transitively – Load – Procedure calls on entry: + formal args -> actual params on exit: + actual arg -> returned object - pointers on stack frame, applies transitively More? • Important property – once an object becomes unreachable, stays unreachable! Carnegie Mellon CS243: Garbage Collection 4 M. Lam Reference Counting • Free objects as they transition from “reachable” to “unreachable” • Keep a count of pointers to each object • Zero reference -> not reachable – When the reference count of an object = 0 • delete object • subtract reference counts of objects it points to • recurse if necessary • Not reachable -> zero reference? answer? – Cyclic data structures • Cost – overhead for each statement that changes ref.