Managing Code Complexity in Asynchronous, Distributed Server Architectures
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												  The Early History of SmalltalkThe 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.
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												  CSE421 Midterm Solutions —SOLUTION SET— 09 Mar 2012CSE421 Midterm Solutions —SOLUTION SET— 09 Mar 2012 This midterm exam consists of three types of questions: 1. 10 multiple choice questions worth 1 point each. These are drawn directly from lecture slides and intended to be easy. 2. 6 short answer questions worth 5 points each. You can answer as many as you want, but we will give you credit for your best four answers for a total of up to 20 points. You should be able to answer the short answer questions in four or five sentences. 3. 2 long answer questions worth 20 points each. Please answer only one long answer question. If you answer both, we will only grade one. Your answer to the long answer should span a page or two. Please answer each question as clearly and succinctly as possible. Feel free to draw pic- tures or diagrams if they help you to do so. No aids of any kind are permitted. The point value assigned to each question is intended to suggest how to allocate your time. So you should work on a 5 point question for roughly 5 minutes. CSE421 Midterm Solutions 09 Mar 2012 Multiple Choice 1. (10 points) Answer all ten of the following questions. Each is worth one point. (a) In the story that GWA (Geoff) began class with on Monday, March 4th, why was the Harvard student concerned about his grade? p He never attended class. He never arrived at class on time. He usually fell asleep in class. He was using drugs. (b) All of the following are inter-process (IPC) communication mechanisms except p shared files.
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												  Object-Oriented Programming in the Beta Programming LanguageOBJECT-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.
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												  Precise Garbage Collection for CPrecise Garbage Collection for C Jon Rafkind Adam Wick John Regehr Matthew Flatt University of Utah Galois, Inc. University of Utah University of Utah [email protected] [email protected] [email protected] mfl[email protected] Abstract no-ops. The resulting program usually runs about as well as before, Magpie is a source-to-source transformation for C programs that but without the ongoing maintenance burden of manual memory enables precise garbage collection, where precise means that inte- management. In our experience, however, conservative GC works gers are not confused with pointers, and the liveness of a pointer poorly for long-running programs, such as a web server, a program- is apparent at the source level. Precise GC is primarily useful for ming environment, or an operating system kernel. For such pro- long-running programs and programs that interact with untrusted grams, conservative GC can trigger unbounded memory use due to components. In particular, we have successfully deployed precise linked lists [Boehm 2002] that manage threads and continuations; GC in the C implementation of a language run-time system that was this problem is usually due to liveness imprecision [Hirzel et al. originally designed to use conservative GC. We also report on our 2002], rather than type imprecision. Furthermore, the programs experience in transforming parts of the Linux kernel to use precise are susceptible to memory-exhaustion attack from malicious code GC instead of manual memory management. (e.g., user programs or untrusted servlets) that might be otherwise restricted through a sandbox [Wick and Flatt 2004]. Categories and Subject Descriptors D.4.2 [Storage Manage- This paper describes our design of and experience with a GC ment]: Garbage Collection for C that is less conservative.
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												  Man Pages Section 3 Library Interfaces and Headersman pages section 3: Library Interfaces and Headers Part No: 816–5173–16 September 2010 Copyright © 2010, Oracle and/or its affiliates. All rights reserved. This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing. If this is software or related software documentation that is delivered to the U.S. Government or anyone licensing it on behalf of the U.S. Government, the following notice is applicable: U.S. GOVERNMENT RIGHTS Programs, software, databases, and related documentation and technical data delivered to U.S. Government customers are “commercial computer software” or “commercial technical data” pursuant to the applicable Federal Acquisition Regulation and agency-specific supplemental regulations. As such, the use, duplication, disclosure, modification, and adaptation shall be subject to the restrictions and license terms setforth in the applicable Government contract, and, to the extent applicable by the terms of the Government contract, the additional rights set forth in FAR 52.227-19, Commercial Computer Software License (December 2007). Oracle America, Inc., 500 Oracle Parkway, Redwood City, CA 94065.
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												  CPS323 Lecture: Concurrency Materials: 1. Coroutine ProjectablesCPS323 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.
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												  Part I: Unix SignalsPart I: Unix Signals 1 Stopping a Program What if you run this program? int main () { while (1); printf("bye\n"); return 0; } What happens if you hit Ctl-C? Could you make Ctl-C print ªbyeº before exiting? 2-4 Signals A shell handles Ctl-C by sending the SIGINT signal to a process The sigaction() function can be used to install a signal handler See bye.c and bye2.c 5 Some Other Signals SIGHUP terminal is gone SIGQUIT please quit SIGKILL force quit (cannot handle) SIGSEGV seg fault SIGALRM timer expired SIGPIPE write to pipe with closed read end SIGCHLD child completed 6 Timers Use setitimer() to start a timer See timer.c and timer2.c... 7 Signal Handlers and Races Beware! Ð a signal handler is practically a thread Use sigprocmask() to (un)block signals See timer3.c 8 Part II: Deadlock · Conditions · Prevention · Detection 9 Deadlock is when two or more threads are waiting for an event that can only be generated by these same threads printer->Wait(); disk->Wait(); disk->Wait(); printer->Wait(); // copy from disk // copy from disk // to printer // to printer printer->Signal(); printer->Signal(); disk->Signal(); disk->Signal(); Deadlock can occur anytime threads acquire multiple resources (printers, disks, etc.), perform work, and then release their resources 10 Deadlock 11 Deadlock 12 Deadlock Examples · Linux: In-kernel memory allocator runs out of pages, causing an ªout of memory handlerº to run, which calls a function that tries to allocate a page. · Windows 2000: The OS keeps a pool of ªworker threadsº waiting to do work; one worker thread submits a job to another worker thread, but there are no free worker-thread slots.
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												  Automatic Handling of Global Variables for Multi-Threaded MPI ProgramsAutomatic Handling of Global Variables for Multi-threaded MPI Programs Gengbin Zheng, Stas Negara, Celso L. Mendes, Laxmikant V. Kale´ Eduardo R. Rodrigues Department of Computer Science Institute of Informatics University of Illinois at Urbana-Champaign Federal University of Rio Grande do Sul Urbana, IL 61801, USA Porto Alegre, Brazil fgzheng,snegara2,cmendes,[email protected] [email protected] Abstract— necessary to privatize global and static variables to ensure Hybrid programming models, such as MPI combined with the thread-safety of an application. threads, are one of the most efficient ways to write parallel ap- In high-performance computing, one way to exploit multi- plications for current machines comprising multi-socket/multi- core nodes and an interconnection network. Global variables in core platforms is to adopt hybrid programming models that legacy MPI applications, however, present a challenge because combine MPI with threads, where different programming they may be accessed by multiple MPI threads simultaneously. models are used to address issues such as multiple threads Thus, transforming legacy MPI applications to be thread-safe per core, decreasing amount of memory per core, load in order to exploit multi-core architectures requires proper imbalance, etc. When porting legacy MPI applications to handling of global variables. In this paper, we present three approaches to eliminate these hybrid models that involve multiple threads, thread- global variables to ensure thread-safety for an MPI program. safety of the applications needs to be addressed again. These approaches include: (a) a compiler-based refactoring Global variables cause no problem with traditional MPI technique, using a Photran-based tool as an example, which implementations, since each process image contains a sep- automates the source-to-source transformation for programs arate instance of the variable.
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												  A Low-Cost Implementation of Coroutines for CUniversity 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.
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												  Kotlin Coroutines Deep Dive Into Bytecode #WhoamiKotlin Coroutines Deep Dive into Bytecode #whoami ● Kotlin compiler engineer @ JetBrains ● Mostly working on JVM back-end ● Responsible for (almost) all bugs in coroutines code Agenda I will talk about ● State machines ● Continuations ● Suspend and resume I won’t talk about ● Structured concurrency and cancellation ● async vs launch vs withContext ● and other library related stuff Agenda I will talk about Beware, there will be code. A lot of code. ● State machines ● Continuations ● Suspend and resume I won’t talk about ● Structured concurrency and cancellation ● async vs launch vs withContext ● and other library related stuff Why coroutines ● No dependency on a particular implementation of Futures or other such rich library; ● Cover equally the "async/await" use case and "generator blocks"; ● Make it possible to utilize Kotlin coroutines as wrappers for different existing asynchronous APIs (such as Java NIO, different implementations of Futures, etc). via coroutines KEEP Getting Lazy With Kotlin Pythagorean Triples fun printPythagoreanTriples() { for (i in 1 until 100) { for (j in 1 until i) { for (k in i until 100) { if (i * i + j * j < k * k) { break } if (i * i + j * j == k * k) { println("$i^2 + $j^2 == $k^2") } } } } } Pythagorean Triples fun printPythagoreanTriples() { for (i in 1 until 100) { for (j in 1 until i) { for (k in i until 100) { if (i * i + j * j < k * k) { break } if (i * i + j * j == k * k) { println("$i^2 + $j^2 == $k^2") } } } } } Pythagorean Triples fun printPythagoreanTriples() { for (i in 1 until 100) { for (j
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												  Csc 520 Principles of Programming Languages Coroutines CoroutinesCoroutines Coroutines are supported by Simula and Modula-2. CSc 520 They are similar to Java’s threads, except the programmer has to explicitly transfer control from one Principles of Programming execution context to another. Languages Thus, like threads several coroutines can exist simultaneously but unlike threads there is no central 36: Procedures — Coroutines scheduler that decides which coroutine should run next. Christian Collberg A coroutine is represented by a closure. [email protected] A special operation transfer(C) shifts control to the coroutine C, at the location where C last left off. Department of Computer Science University of Arizona Copyright c 2005 Christian Collberg 520—Spring 2005—36 [1] 520—Spring 2005—36 [2] Coroutines. Coroutines. The next slide shows an example from Scott where two var us, cfs: coroutine; coroutines execute “concurrently”, by explicitly transferring control between each other. coroutine update_screen() { ... In the example one coroutine displays a moving detach screen-saver, the other walks the file-system to check loop { for corrupt files. ... transfer(cfs) ... } } coroutine check_file_system() { ... } main () { ... } 520—Spring 2005—36 [3] 520—Spring 2005—36 [4] Coroutines. Coroutines in Modula-2 coroutine check_file_system() { Modula-2's system module provides two functions to create and transfer ... between coroutines: detach for all files do { PROCEDURE NEWPROCESS( proc: PROC; (* The procedure *) ... transfer(cfs) addr: ADDRESS; (* The stack *) ... transfer(cfs) size: CARDINAL; (* The stack size *) ... transfer(cfs) ... VAR new: ADDRESS); (* The coroutine *) } PROCEDURE TRANSFER( } VAR source: ADDRESS; (* Current coroutine *) VAR destination: ADDRESS); (* New coroutine *) main () { us := new update_screen(); The ®rst time TRANSFER is called source will be instantiated to cfs := new check_file_system(); the main (outermost) coroutine.
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												  Threading and GUI Issues for RThreading 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.