DOCSLIB.ORG

Actor-Oriented Programming for Wireless Sensor Networks

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Actor-Oriented Programming for Wireless Sensor Networks Actor-Oriented Programming for Wireless Sensor Networks Elaine Cheong Electrical Engineering and Computer Sciences University of California at Berkeley Technical Report No. UCB/EECS-2007-112 http://www.eecs.berkeley.edu/Pubs/TechRpts/2007/EECS-2007-112.html August 30, 2007 Copyright © 2007, by the author(s). All rights reserved. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. Actor-Oriented Programming for Wireless Sensor Networks by Elaine Cheong B.S. (University of Maryland, College Park) 2000 M.S. (University of California, Berkeley) 2003 A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Engineering – Electrical Engineering and Computer Sciences in the GRADUATE DIVISION of the UNIVERSITY OF CALIFORNIA, BERKELEY Committee in charge: Professor Edward A. Lee, Chair Professor Eric A. Brewer Professor Paul K. Wright Fall 2007 Actor-Oriented Programming for Wireless Sensor Networks Copyright 2007 by Elaine Cheong 1 Abstract Actor-Oriented Programming for Wireless Sensor Networks by Elaine Cheong Doctor of Philosophy in Engineering – Electrical Engineering and Computer Sciences University of California, Berkeley Professor Edward A. Lee, Chair Wireless sensor networks is an emerging area of embedded systems that has the potential to revolutionize our lives at home and at work, with wide-ranging applications, including environmen- tal monitoring and conservation, manufacturing and industrial control, business asset management, seismic and structural monitoring, transportation, health care, and home automation. Building sen- sor networks today requires piecing together a variety of hardware and software components, each with different design methodologies and tools, making it a challenging and error-prone process. In this dissertation, I advocate using an actor-oriented approach to designing, generating, pro- gramming, and simulating wireless sensor network applications. Actor-oriented programming pro- vides a common high-level language that unifies the programming interface between the operating system, node-centric, middleware, and macroprogramming layers of a sensor network application. This dissertation presents the TinyGALS (Globally Asynchronous, Locally Synchronous) pro- gramming model, which is built on the TinyOS programming model. TinyGALS is implemented in the galsC programming language, which provides constructs to systematically build concurrent tasks called actors. The galsC compiler toolsuite provides high-level type checking and code gen- eration facilities and allows developers to deploy actor-oriented programs on actual sensor node hardware. This dissertation then describes Viptos (Visual Ptolemy and TinyOS), a joint modeling and design environment for wireless networks and sensor node software. Viptos is built on Ptolemy II, an actor-oriented graphical modeling and simulation environment for embedded systems, and TOSSIM, an interrupt-level discrete-event simulator for TinyOS networks. This dissertation also presents methods for using higher-order actors with various metapro- 2 gramming and generative programming techniques that enable wireless sensor network application developers to create high-level, parameterizable descriptions and automatically generate sensor net- work simulation scenarios from these models. All of the tools I developed and describe in this dissertation are open-source and freely available on the web. The networked embedded computing community can use these tools and the knowledge shared in this dissertation to improve the way we program wireless sensor networks. Professor Edward A. Lee Dissertation Committee Chair i To the teachers who have challenged, encouraged, and guided me through life. ii Café Ptolemy Executive Chefs: Elaine Cheong and Andrew Mihal Appetizers Avocado Smash and Double-Decker Baked Quesadillas Corn Pancakes with Green Onions, Actors, Crème Fraîche, Avocado, and Cherry Tomatoes Salads Fuyu Persimmon, Avocado & Watercress Salad with Discrete-Event Miso Dressing Corn and Cherry Tomato Salad with Arugula Soups Mexican Chicken Soup Butternut Squash Bisque Why-the-Chicken-Crossed-the-Model Santa Fe-Tastic Tortilla Soup Entrees Chicken Pot Pie Fettuccine with Concurrent Meyer Lemon Butter Sauce Chicken Tikka Masala Farfalle with Ptalon Pesto, Feta, and Cherry Tomatoes Butternut Squash Lasagna Cumin Crusted Chicken with Cotija and Mango-Garlic Sauce with Green Onion Pesto Mashed Motes Butternut Squash, Metacabbage & Pancetta Risotto with Basil Oil Desserts Marillenknödel: Austrian apricot dumplings Zwetschgendatschi: Bavarian plum delicacy Drinks Plum Granita with Limoncello Vinho do IOPorto Lychee-flavoured Ramune (ラムネ) iii Contents List of Figures vi List of Tables viii 1 Introduction 1 1.1 Wireless Sensor Networks .............................. 2 1.2 Actor-Oriented Programming ............................. 3 1.3 Actor-Oriented Programming for Wireless Sensor Networks ............ 5 1.4 Previously Published Work .............................. 8 2 Background 9 2.1 TinyOS ........................................ 9 2.1.1 NesC syntax ................................. 10 2.1.2 TinyOS execution model ........................... 10 2.2 Ptolemy II ....................................... 11 2.2.1 VisualSense .................................. 14 2.3 Summary ....................................... 17 3 TinyGALS and galsC 19 3.1 The TinyGALS Programming Model and galsC Language ............. 22 3.1.1 Programming constructs and language syntax ................ 22 3.1.2 Execution model and language semantics .................. 28 3.1.3 Link model within actors ........................... 36 3.1.4 Type inference and type checking ...................... 38 3.1.5 Summary ................................... 39 3.2 Concurrency and Determinacy Issues ......................... 40 3.2.1 Concurrency ................................. 40 3.2.2 Determinacy ................................. 41 3.2.3 Summary ................................... 48 3.3 Code Generation ................................... 49 3.3.1 Links and connections ............................ 51 3.3.2 Communication ................................ 51 3.3.3 TinyGUYS .................................. 53 3.3.4 System initialization and start of execution ................. 53 iv 3.3.5 Scheduling .................................. 53 3.3.6 Memory usage ................................ 55 3.4 Example ........................................ 55 3.5 Summary ....................................... 57 4 Viptos 59 4.1 Design ......................................... 62 4.1.1 Representation of nesC components ..................... 62 4.1.2 Transformation of nesC components ..................... 64 4.1.3 Generation of code for target deployment .................. 66 4.1.4 Generation of code for simulation ...................... 68 4.1.5 Simulation of TinyOS in Viptos ....................... 69 4.2 Performance Evaluation ................................ 74 4.2.1 Comparison to TOSSIM ........................... 77 4.2.2 Radio ..................................... 78 4.3 Summary ....................................... 79 5 Metaprogramming for Wireless Sensor Networks 81 5.1 Generative Programming and Metaprogramming .................. 81 5.2 Higher-order Functions, Actors, and Components .................. 82 5.3 Ptalon ......................................... 84 5.3.1 A simple example .............................. 84 5.3.2 Reconfiguration in Ptalon .......................... 86 5.4 Specifying WSN Applications Programmatically .................. 89 5.4.1 Motivation .................................. 89 5.4.2 Small World ................................. 90 5.4.3 Parameter Sweep ............................... 90 5.4.4 Higher-order actors .............................. 95 5.4.5 Discussion .................................. 98 5.5 Summary ....................................... 102 6 Related Work 105 6.1 TinyGALS and galsC ................................. 105 6.1.1 Non-blocking ................................. 105 6.1.2 MPI ...................................... 106 6.1.3 Port-Based Objects .............................. 108 6.1.4 Click ..................................... 110 6.1.5 Click and Ptolemy II ............................. 118 6.1.6 Timed Multitasking .............................. 118 6.2 Design, Simulation, and Deployment Environments ................. 119 6.2.1 Design and simulation environments ..................... 119 6.2.2 TinyOS development and editing environments ............... 123 6.2.3 Programming and deployment environments ................ 123 6.3 Summary ....................................... 124 v 7 Conclusion 125 Bibliography 127 vi List of Figures 1.1 Object-oriented design vs. actor-oriented design. Source: Edward A. Lee. ..... 5 1.2 WSN landscape. .................................... 6 2.1 Sample nesC source code. .............................. 11 2.2 Illustration of an actor-oriented model (top) in Ptolemy II and its hierarchical ab- straction (bottom). ................................... 13 2.3 XML representation of the Sinewave source. .................... 15 3.1 Graphical representation of the SenseTag
Load more

Recommended publications
  • Riscv-Software-Stack-Tutorial-Hpca2015
    Software Tools Bootcamp RISC-V ISA Tutorial — HPCA-21 08 February 2015 Albert Ou UC Berkeley [email protected] Preliminaries To follow along, download these slides at http://riscv.org/tutorial-hpca2015.html 2 Preliminaries . Shell commands are prefixed by a “$” prompt. Due to time constraints, we will not be building everything from source in real-time. - Binaries have been prepared for you in the VM image. - Detailed build steps are documented here for completeness but are not necessary if using the VM. Interactive portions of this tutorial are denoted with: $ echo 'Hello world' . Also as a reminder, these slides are marked with an icon in the upper-right corner: 3 Software Stack . Many possible combinations (and growing) . But here we will focus on the most common workflows for RISC-V software development 4 Agenda 1. riscv-tools infrastructure 2. First Steps 3. Spike + Proxy Kernel 4. QEMU + Linux 5. Advanced Cross-Compiling 6. Yocto/OpenEmbedded 5 riscv-tools — Overview “Meta-repository” with Git submodules for every stable component of the RISC-V software toolchain Submodule Contents riscv-fesvr RISC-V Frontend Server riscv-isa-sim Functional ISA simulator (“Spike”) riscv-qemu Higher-performance ISA simulator riscv-gnu-toolchain binutils, gcc, newlib, glibc, Linux UAPI headers riscv-llvm LLVM, riscv-clang submodule riscv-pk RISC-V Proxy Kernel (riscv-linux) Linux/RISC-V kernel port riscv-tests ISA assembly tests, benchmark suite All listed submodules are hosted under the riscv GitHub organization: https://github.com/riscv 6 riscv-tools — Installation . Build riscv-gnu-toolchain (riscv*-*-elf / newlib target), riscv-fesvr, riscv-isa-sim, and riscv-pk: (pre-installed in VM) $ git clone https://github.com/riscv/riscv-tools $ cd riscv-tools $ git submodule update --init --recursive $ export RISCV=<installation path> $ export PATH=${PATH}:${RISCV}/bin $ ./build.sh .
    [Show full text]
  • Operating Systems and Applications for Embedded Systems >>> Toolchains
    >>> Operating Systems And Applications For Embedded Systems >>> Toolchains Name: Mariusz Naumowicz Date: 31 sierpnia 2018 [~]$ _ [1/19] >>> Plan 1. Toolchain Toolchain Main component of GNU toolchain C library Finding a toolchain 2. crosstool-NG crosstool-NG Installing Anatomy of a toolchain Information about cross-compiler Configruation Most interesting features Sysroot Other tools POSIX functions AP [~]$ _ [2/19] >>> Toolchain A toolchain is the set of tools that compiles source code into executables that can run on your target device, and includes a compiler, a linker, and run-time libraries. [1. Toolchain]$ _ [3/19] >>> Main component of GNU toolchain * Binutils: A set of binary utilities including the assembler, and the linker, ld. It is available at http://www.gnu.org/software/binutils/. * GNU Compiler Collection (GCC): These are the compilers for C and other languages which, depending on the version of GCC, include C++, Objective-C, Objective-C++, Java, Fortran, Ada, and Go. They all use a common back-end which produces assembler code which is fed to the GNU assembler. It is available at http://gcc.gnu.org/. * C library: A standardized API based on the POSIX specification which is the principle interface to the operating system kernel from applications. There are several C libraries to consider, see the following section. [1. Toolchain]$ _ [4/19] >>> C library * glibc: Available at http://www.gnu.org/software/libc. It is the standard GNU C library. It is big and, until recently, not very configurable, but it is the most complete implementation of the POSIX API. * eglibc: Available at http://www.eglibc.org/home.
    [Show full text]
  • Linux Journal | February 2016 | Issue
    ™ A LOOK AT KDE’s KStars Astronomy Program Since 1994: The Original Magazine of the Linux Community FEBRUARY 2016 | ISSUE 262 | www.linuxjournal.com + Programming Working with Command How-Tos Arguments in Your Program a Shell Scripts BeagleBone Interview: Katerina Black Barone-Adesi on to Help Brew Beer Developing the Snabb Switch Network Write a Toolkit Short Script to Solve a WATCH: ISSUE Math Puzzle OVERVIEW V LJ262-February2016.indd 1 1/21/16 5:26 PM NEW! Agile Improve Product Business Development Processes with an Enterprise Practical books Author: Ted Schmidt Job Scheduler for the most technical Sponsor: IBM Author: Mike Diehl Sponsor: people on the planet. Skybot Finding Your DIY Way: Mapping Commerce Site Your Network Author: to Improve Reuven M. Lerner Manageability GEEK GUIDES Sponsor: GeoTrust Author: Bill Childers Sponsor: InterMapper Combating Get in the Infrastructure Fast Lane Sprawl with NVMe Author: Author: Bill Childers Mike Diehl Sponsor: Sponsor: Puppet Labs Silicon Mechanics & Intel Download books for free with a Take Control Linux in simple one-time registration. of Growing the Time Redis NoSQL of Malware http://geekguide.linuxjournal.com Server Clusters Author: Author: Federico Kereki Reuven M. Lerner Sponsor: Sponsor: IBM Bit9 + Carbon Black LJ262-February2016.indd 2 1/21/16 5:26 PM NEW! Agile Improve Product Business Development Processes with an Enterprise Practical books Author: Ted Schmidt Job Scheduler for the most technical Sponsor: IBM Author: Mike Diehl Sponsor: people on the planet. Skybot Finding Your DIY Way: Mapping Commerce Site Your Network Author: to Improve Reuven M. Lerner Manageability GEEK GUIDES Sponsor: GeoTrust Author: Bill Childers Sponsor: InterMapper Combating Get in the Infrastructure Fast Lane Sprawl with NVMe Author: Author: Bill Childers Mike Diehl Sponsor: Sponsor: Puppet Labs Silicon Mechanics & Intel Download books for free with a Take Control Linux in simple one-time registration.
    [Show full text]
  • Compiler Construction
    Compiler Construction Chapter 11 Compiler Construction Compiler Construction 1 A New Compiler • Perhaps a new source language • Perhaps a new target for an existing compiler • Perhaps both Compiler Construction Compiler Construction 2 Source Language • Larger, more complex languages generally require larger, more complex compilers • Is the source language expected to evolve? – E.g., Java 1.0 ! Java 1.1 ! . – A brand new language may undergo considerable change early on – A small working prototype may be in order – Compiler writers must anticipate some amount of change and their design must therefore be flexible – Lexer and parser generators (like Lex and Yacc) are therefore better than hand- coding the lexer and parser when change is inevitable Compiler Construction Compiler Construction 3 Target Language • The nature of the target language and run-time environment influence compiler construction considerably • A new processor and/or its assembler may be buggy Buggy targets make it difficult to debug compilers for that target! • A successful source language will persist over several target generations – E.g., 386 ! 486 ! Pentium ! . – Thus the design of the IR is important – Modularization of machine-specific details is also important Compiler Construction Compiler Construction 4 Compiler Performance Issues • Compiler speed • Generated code quality • Error diagnostics • Portability • Maintainability Compiler Construction Compiler Construction 5 Compiler Speed • Reduce the number of modules • Reduce the number of passes Perhaps generate machine
    [Show full text]
  • A Model-Driven Development and Verification Approach
    A MODEL-DRIVEN DEVELOPMENT AND VERIFICATION APPROACH FOR MEDICAL DEVICES by Jakub Jedryszek B.S., Wroclaw University of Technology, Poland, 2012 B.A., Wroclaw University of Economics, Poland, 2012 A THESIS submitted in partial fulfillment of the requirements for the degree MASTER OF SCIENCE Department of Computing and Information Sciences College of Engineering KANSAS STATE UNIVERSITY Manhattan, Kansas 2014 Approved by: Major Professor John Hatcliff Abstract Medical devices are safety-critical systems whose failure may put human life in danger. They are becoming more advanced and thus more complex. This leads to bigger and more complicated code-bases that are hard to maintain and verify. Model-driven development provides high-level and abstract description of the system in the form of models that omit details, which are not relevant during the design phase. This allows for certain types of verification and hazard analysis to be performed on the models. These models can then be translated into code. However, errors that do not exist in the models may be introduced during the implementation phase. Automated translation from verified models to code may prevent to some extent. This thesis proposes approach for model-driven development and verification of medi- cal devices. Models are created in AADL (Architecture Analysis & Design Language), a language for software and hardware architecture modeling. AADL models are translated to SPARK Ada, contract-based programming language, which is suitable for software veri- fication. Generated code base is further extended by developers to implement internals of specific devices. Created programs can be verified using SPARK tools. A PCA (Patient Controlled Analgesia) pump medical device is used to illustrate the primary artifacts and process steps.
    [Show full text]
  • Linux Everywhere a Look at Linux Outside the World of Desktops
    Linux Everywhere A look at Linux outside the world of desktops CIS 191 Spring 2012 – Guest Lecture by Philip Peng Lecture Outline 1. Introduction 2. Different Platforms 3. Reasons for Linux 4. Cross-compiling 5. Case Study: iPodLinux 6. Questions 2 What’s in common? 3 All your hardware are belong to us • Linux is everywhere – If its programmable, you can put Linux on it! – Yes, even a microwave CES 2010, microwave running Android: http://www.handlewithlinux.com/linux-washing-cooking 4 Servers • What servers use – Stability, security, free – Examples: ◦ CentOS ◦ Debian ◦ Red Hat 5 Desktop • What you use – Free Windows/Mac alternative – Examples: ◦ Ubuntu ◦ Fedora ◦ PCLinuxOS 6 Gaming Devices • What (white-hat) hackers do – To run “homebrew” software – Examples: ◦ PS3, Wii, XBOX ◦ PS2, GameCube ◦ Dreamcast ◦ PSP, DS ◦ Open Pandora, GP2X 7 Mobile Devices • What distributors are developing – Community contribution – Examples ◦ Android ◦ Maemo/MeeGo/Tizen ◦ Openmoko 8 Embedded Devices • What embedded hardware run – Small footprint, dev tools – Examples ◦ RTLinux (real-time) ◦ μClinux (no MMU) ◦ Ångström (everything) 9 Why? 10 Free! • Free! – As in freedom, i.e. open source – As in beer, i.e. vs paid upgrades 11 Homebrew! • Run own software – Your hardware your software? 12 Support! • Community contribution – “For the greater good” (i.e. users) – Everyone contributes ◦ Specialists from all over the world – Existing hardware support ◦ Many already supported computer architecture ◦ Modify existing drivers 13 Lots of support! 14 Why not? • Because we can – If its hackable, it can run Linux 15 How? • How do we get Linux running on XXX? • Port: A version of software modified to run on a different target platform – The PS3 port of Fedora is a modified build of Fedora compiled to run on the PS3 architecture – e.g.
    [Show full text]
  • Embedded Linux Device Driver Development Sébastien Bilavarn
    Embedded Linux Device driver development Sébastien Bilavarn Polytech’Nice Sophia - Département Electronique - Université de Nice Sophia Antipolis - S. Bilavarn - 1 - Outline Ch1 – Introduction to Linux Ch2 – Linux kernel overview Ch3 – Linux for Embedded Systems Ch4 – Embedded Linux distributions Ch5 – Case study: Xilinx PowerPC Linux Ch5 bis – Case study: Xilinx Zynq-7000 Linux Ch6 – Device driver development Polytech’Nice Sophia - Département Electronique - Université de Nice Sophia Antipolis - S. Bilavarn - 2 - Linux for Embedded Systems Introduction to Embedded Linux Key features Embedded Linux development Linux kernel development Polytech’Nice Sophia - Département Electronique - Université de Nice Sophia Antipolis - S. Bilavarn - 3 - Embedded Linux What is Embedded Linux ? Strictly speaking Embedded Linux is an operating system based on Linux and adapted specifically to the constraints of embedded systems. Unlike standard versions of Linux for Personal Computers, embedded Linux is designed for systems with limited resources Memory: few RAM, sometimes no Memory Management Unit (MMU) Storage: Flash instead of hard disk drive Since embedded systems are often designed for domain specific purposes and specific target platforms, they use kernel versions that are optimized for a given context of application. This results in different Linux kernel variants that are also called Linux distributions Polytech’Nice Sophia - Département Electronique - Université de Nice Sophia Antipolis - S. Bilavarn - 4 - Embedded Linux What is embedded Linux ? Embedded Linux is used in embedded systems such as mobile phones, personal digital assistants (PDA), media players set-top boxes, and other consumer electronics devices networking equipment machine control, industrial automation navigation equipment medical instruments Key features runs in a small embedded system, typically booting out of Flash, no hard disk drive, no full-size video display, and take far less than 2 minutes to boot up, sometimes supports real- time tasks.
    [Show full text]
  • Cross-Compiler Bipartite Vulnerability Search
    electronics Article Cross-Compiler Bipartite Vulnerability Search Paul Black * and Iqbal Gondal Internet Commerce Security Laboratory (ICSL), Federation University, Ballarat 3353, Australia; [email protected] * Correspondence: [email protected] Abstract: Open-source libraries are widely used in software development, and the functions from these libraries may contain security vulnerabilities that can provide gateways for attackers. This paper provides a function similarity technique to identify vulnerable functions in compiled programs and proposes a new technique called Cross-Compiler Bipartite Vulnerability Search (CCBVS). CCBVS uses a novel training process, and bipartite matching to filter SVM model false positives to improve the quality of similar function identification. This research uses debug symbols in programs compiled from open-source software products to generate the ground truth. This automatic extraction of ground truth allows experimentation with a wide range of programs. The results presented in the paper show that an SVM model trained on a wide variety of programs compiled for Windows and Linux, x86 and Intel 64 architectures can be used to predict function similarity and that the use of bipartite matching substantially improves the function similarity matching performance. Keywords: malware similarity; function similarity; binary similarity; machine-learning; bipar- tite matching 1. Introduction Citation: Black, P.; Gondal, I. Cross-Compiler Bipartite Function similarity techniques are used in the following activities, the triage of mal- Vulnerability Search. Electronics 2021, ware [1], analysis of program patches [2], identification of library functions [3], analysis of 10, 1356. https://doi.org/10.3390/ code authorship [4], the identification of similar function pairs to reduce manual analysis electronics10111356 workload, [5], plagiarism analysis [6], and for vulnerable function identification [7–9].
    [Show full text]
  • COSMIC C Cross Compiler for Stmicroelectronics ST7 Family
    COSMIC C Cross Compiler for STMicroelectronics ST7 Family COSMIC’s C cross compiler, cxST7 for the STMicroelectronics ST7 family of microcontrollers, incorporates over fifteen years of innovative design and development effort. Used in the field since 1997, cxST7 is reliable, field-proven, and incorporates many features to help ensure your embedded ST7 design meets and exceeds performance specifications. The C Compiler package for Windows includes: COSMIC integrated development environment (IDEA), optimizing C cross compiler, macro assembler, linker, librarian, object inspector, hex file generator, object format converters, debugging support utilities, run-time libraries and a compiler command driver. The PC compiler package runs under Windows 95/98/ME/NT4/2000 and XP.. Key Features Microcontroller-Specific Design Supports All ST7 Family Microcontrollers cxST7, is designed specifically for the STMicroelectronics ST7 family of microcontrollers; all ST7 family processors are ANSI C Implementation supported. A special code generator and optimizer targeted for the ST7 family eliminates the overhead and complexity of Extensions to ANSI for Embedded Systems a more generic compiler. You also get header file support for Global and Processor-Specific Optimizations many of the popular ST7 peripherals, so you can access their memory mapped objects by name either at the C or assembly Optimized Function Calling language levels. Debug Fully Optimized Code ANSI / ISO Standard C Automatic Checksums This implementation conforms with the ANSI and ISO Real and Simulated Stack models Standard C syntax specifications which helps you protect Smart Linker optimizes RAM usage your software investment by aiding code portability and reliability. C support for Zero Page Data C support for Interrupt Handlers Flexible User Interface The Cosmic C compiler can be used with the included Three In-Line Assembly Methods Windows IDEA or as a Windows 32-bit command line Assembler Supports C #defines and #includes application for use with your favorite editor, make or source code control system.
    [Show full text]
  • GNAT User's Guide
    GNAT User's Guide GNAT, The GNU Ada Compiler For gcc version 4.7.4 (GCC) AdaCore Copyright c 1995-2009 Free Software Foundation, Inc. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.3 or any later version published by the Free Software Foundation; with no Invariant Sections, with no Front-Cover Texts and with no Back-Cover Texts. A copy of the license is included in the section entitled \GNU Free Documentation License". About This Guide 1 About This Guide This guide describes the use of GNAT, a compiler and software development toolset for the full Ada programming language. It documents the features of the compiler and tools, and explains how to use them to build Ada applications. GNAT implements Ada 95 and Ada 2005, and it may also be invoked in Ada 83 compat- ibility mode. By default, GNAT assumes Ada 2005, but you can override with a compiler switch (see Section 3.2.9 [Compiling Different Versions of Ada], page 78) to explicitly specify the language version. Throughout this manual, references to \Ada" without a year suffix apply to both the Ada 95 and Ada 2005 versions of the language. What This Guide Contains This guide contains the following chapters: • Chapter 1 [Getting Started with GNAT], page 5, describes how to get started compiling and running Ada programs with the GNAT Ada programming environment. • Chapter 2 [The GNAT Compilation Model], page 13, describes the compilation model used by GNAT. • Chapter 3 [Compiling Using gcc], page 41, describes how to compile Ada programs with gcc, the Ada compiler.
    [Show full text]
  • Kotlin Coroutines Deep Dive Into Bytecode #Whoami
    Kotlin 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
    [Show full text]
  • Contention in Structured Concurrency: Provably Efficient Dynamic Non-Zero Indicators for Nested Parallelism
    Contention in Structured Concurrency: Provably Efficient Dynamic Non-Zero Indicators for Nested Parallelism Umut A. Acar1;2 Naama Ben-David 1 Mike Rainey 2 January 16, 2017 CMU-CS-16-133 School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 A short version of this work appears in the proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming 2017 (PPoPP '17). 1Carnegie Mellon University, Pittsburgh, PA 2Inria-Paris Keywords: concurrent data structures, non-blocking data structures, contention, nested parallelism, dependency counters Abstract Over the past two decades, many concurrent data structures have been designed and im- plemented. Nearly all such work analyzes concurrent data structures empirically, omit- ting asymptotic bounds on their efficiency, partly because of the complexity of the analysis needed, and partly because of the difficulty of obtaining relevant asymptotic bounds: when the analysis takes into account important practical factors, such as contention, it is difficult or even impossible to prove desirable bounds. In this paper, we show that considering structured concurrency or relaxed concurrency mod- els can enable establishing strong bounds, also for contention. To this end, we first present a dynamic relaxed counter data structure that indicates the non-zero status of the counter. Our data structure extends a recently proposed data structure, called SNZI, allowing our structure to grow dynamically in response to the increasing degree of concurrency in the system. Using the dynamic SNZI data structure, we then present a concurrent data structure for series-parallel directed acyclic graphs (sp-dags), a key data structure widely used in the implementation of modern parallel programming languages.
    [Show full text]