Java Concurrency in Practice
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Pdp11-40.Pdf
processor handbook digital equipment corporation Copyright© 1972, by Digital Equipment Corporation DEC, PDP, UNIBUS are registered trademarks of Digital Equipment Corporation. ii TABLE OF CONTENTS CHAPTER 1 INTRODUCTION 1·1 1.1 GENERAL ............................................. 1·1 1.2 GENERAL CHARACTERISTICS . 1·2 1.2.1 The UNIBUS ..... 1·2 1.2.2 Central Processor 1·3 1.2.3 Memories ........... 1·5 1.2.4 Floating Point ... 1·5 1.2.5 Memory Management .............................. .. 1·5 1.3 PERIPHERALS/OPTIONS ......................................... 1·5 1.3.1 1/0 Devices .......... .................................. 1·6 1.3.2 Storage Devices ...................................... .. 1·6 1.3.3 Bus Options .............................................. 1·6 1.4 SOFTWARE ..... .... ........................................... ............. 1·6 1.4.1 Paper Tape Software .......................................... 1·7 1.4.2 Disk Operating System Software ........................ 1·7 1.4.3 Higher Level Languages ................................... .. 1·7 1.5 NUMBER SYSTEMS ..................................... 1-7 CHAPTER 2 SYSTEM ARCHITECTURE. 2-1 2.1 SYSTEM DEFINITION .............. 2·1 2.2 UNIBUS ......................................... 2-1 2.2.1 Bidirectional Lines ...... 2-1 2.2.2 Master-Slave Relation .. 2-2 2.2.3 Interlocked Communication 2-2 2.3 CENTRAL PROCESSOR .......... 2-2 2.3.1 General Registers ... 2-3 2.3.2 Processor Status Word ....... 2-4 2.3.3 Stack Limit Register 2-5 2.4 EXTENDED INSTRUCTION SET & FLOATING POINT .. 2-5 2.5 CORE MEMORY . .... 2-6 2.6 AUTOMATIC PRIORITY INTERRUPTS .... 2-7 2.6.1 Using the Interrupts . 2-9 2.6.2 Interrupt Procedure 2-9 2.6.3 Interrupt Servicing ............ .. 2-10 2.7 PROCESSOR TRAPS ............ 2-10 2.7.1 Power Failure .............. -
Multithreading (Concurrency) in Java “Some People, When Confronted
Multithreading (Concurrency) in Java “Some people, when confronted with a problem, think, "I know, I’ll use threads," and then two they hav erpoblesms.” — Ned Batchelder Multi-tasking In the beginning, computers ran in batch mode: a single program with total access to all resources. Later, a multi-tasking operating system enabled multiple (independent) jobs to run (more or less) simultaneously, even though there was only a single CPU. The jobs take turns running some of their code at one time. This type of interleaving of jobs is called concurrency. Multitasking is performing two or more tasks (or jobs) at roughly the same time. Nearly all operating systems are capable of multitasking by using one of two multitasking techniques: process-based multitasking and thread-based multitasking. Each running job was (and sometimes still is) called a process, which has state (a collection of data and handles to system resources such as files and devices) and a single sequence of instructions. It turns out that many tasks are easier to write, debug, and manage if organized as multiple copies of a process (e.g., a web server). Processes are sometimes called tasks, threads, or jobs. (Although there are some distinctions between these concepts, we will ignore them for now.) Time slice, (context) switching, and scheduling are operating system (“OS”) terms related to multi-tasking. The amount of time a task is allowed to use the CPU exclusively is called a time slice, typically 10ms (a hundredth of a second) but can vary depending on your OS and other factors from 1ms to more than 120ms. -
Embedded C Programming I (Ecprogrami)
To our customers, Old Company Name in Catalogs and Other Documents On April 1st, 2010, NEC Electronics Corporation merged with Renesas Technology Corporation, and Renesas Electronics Corporation took over all the business of both companies. Therefore, although the old company name remains in this document, it is a valid Renesas Electronics document. We appreciate your understanding. Renesas Electronics website: http://www.renesas.com April 1st, 2010 Renesas Electronics Corporation Issued by: Renesas Electronics Corporation (http://www.renesas.com) Send any inquiries to http://www.renesas.com/inquiry. Notice 1. All information included in this document is current as of the date this document is issued. Such information, however, is subject to change without any prior notice. Before purchasing or using any Renesas Electronics products listed herein, please confirm the latest product information with a Renesas Electronics sales office. Also, please pay regular and careful attention to additional and different information to be disclosed by Renesas Electronics such as that disclosed through our website. 2. Renesas Electronics does not assume any liability for infringement of patents, copyrights, or other intellectual property rights of third parties by or arising from the use of Renesas Electronics products or technical information described in this document. No license, express, implied or otherwise, is granted hereby under any patents, copyrights or other intellectual property rights of Renesas Electronics or others. 3. You should not alter, modify, copy, or otherwise misappropriate any Renesas Electronics product, whether in whole or in part. 4. Descriptions of circuits, software and other related information in this document are provided only to illustrate the operation of semiconductor products and application examples. -
Lecture 4 Resource Protection and Thread Safety
Concurrency and Correctness – Resource Protection and TS Lecture 4 Resource Protection and Thread Safety 1 Danilo Piparo – CERN, EP-SFT Concurrency and Correctness – Resource Protection and TS This Lecture The Goals: 1) Understand the problem of contention of resources within a parallel application 2) Become familiar with the design principles and techniques to cope with it 3) Appreciate the advantage of non-blocking techniques The outline: § Threads and data races: synchronisation issues § Useful design principles § Replication, atomics, transactions and locks § Higher level concrete solutions 2 Danilo Piparo – CERN, EP-SFT Concurrency and Correctness – Resource Protection and TS Threads and Data Races: Synchronisation Issues 3 Danilo Piparo – CERN, EP-SFT Concurrency and Correctness – Resource Protection and TS The Problem § Fastest way to share data: access the same memory region § One of the advantages of threads § Parallel memory access: delicate issue - race conditions § I.e. behaviour of the system depends on the sequence of events which are intrinsically asynchronous § Consequences, in order of increasing severity § Catastrophic terminations: segfaults, crashes § Non-reproducible, intermittent bugs § Apparently sane execution but data corruption: e.g. wrong value of a variable or of a result Operative definition: An entity which cannot run w/o issues linked to parallel execution is said to be thread-unsafe (the contrary is thread-safe) 4 Danilo Piparo – CERN, EP-SFT Concurrency and Correctness – Resource Protection and TS To Be Precise: Data Race Standard language rules, §1.10/4 and /21: • Two expression evaluations conflict if one of them modifies a memory location (1.7) and the other one accesses or modifies the same memory location. -
Operating Systems What Is an Operating System Real-Time
Operating Systems Babak Kia Adjunct Professor Boston University College of Engineering Email: bkia -at- bu.edu ENG SC757 - Advanced Microprocessor Design What is an Operating System z Operating System handles • Memory Addressing & Management • Interrupt & Exception Handling • Process & Task Management • File System • Timing • Process Scheduling & Synchronization z Examples of Operating Systems • RTOS – Real-Time Operating System • Single-user, Single-task: example PalmOS • Single-user, Multi-task: MS Windows and MacOS • Multi-user, Multi-task: UNIX 2 Real-Time Operating Systems z Operating systems come in two flavors, real-time versus non real-time z The difference between the two is characterized by the consequences which result if functional correctness and timing parameters are not met in the case of real-time operating systems z Real-time operating systems themselves have two varieties, soft real-time systems and hard real- time systems z Examples of real-time systems: • Food processing • Engine Controls • Anti-lock breaking systems 3 1 Soft versus Hard Real-Time z In a soft real-time system, tasks are completed as fast as possible without having to be completed within a specified timeframe z In a hard real-time operating system however, not only must tasks be completed within the specified timeframe, but they must also be completed correctly 4 Foreground/Background Systems z The simplest forms of a non real-time operating systems are comprised of super-loops and are called foreground/background systems z Essentially this is an application -
Clojure, Given the Pun on Closure, Representing Anything Specific
dynamic, functional programming for the JVM “It (the logo) was designed by my brother, Tom Hickey. “It I wanted to involve c (c#), l (lisp) and j (java). I don't think we ever really discussed the colors Once I came up with Clojure, given the pun on closure, representing anything specific. I always vaguely the available domains and vast emptiness of the thought of them as earth and sky.” - Rich Hickey googlespace, it was an easy decision..” - Rich Hickey Mark Volkmann [email protected] Functional Programming (FP) In the spirit of saying OO is is ... encapsulation, inheritance and polymorphism ... • Pure Functions • produce results that only depend on inputs, not any global state • do not have side effects such as Real applications need some changing global state, file I/O or database updates side effects, but they should be clearly identified and isolated. • First Class Functions • can be held in variables • can be passed to and returned from other functions • Higher Order Functions • functions that do one or both of these: • accept other functions as arguments and execute them zero or more times • return another function 2 ... FP is ... Closures • main use is to pass • special functions that retain access to variables a block of code that were in their scope when the closure was created to a function • Partial Application • ability to create new functions from existing ones that take fewer arguments • Currying • transforming a function of n arguments into a chain of n one argument functions • Continuations ability to save execution state and return to it later think browser • back button 3 .. -
Reentrant Code
Reentrant Code a reentrant procedure can have several calls open to it at the same time in an interrupt environment, different ISRs may call the same routine in a multitasking or multiuser or multithreaded environment, a single copy of a subroutine may be shared by more than one task/user/thread Reentrant Task subroutine A Task B Reentrant Code Characteristics requirements: 1. any parameters or local variables must be on the stack frame 2. registers may be used for parameters and local variables but must be saved on or restored from the stack at beginning/end of the subroutine 3. guarantee that each call of the subroutine will create a separate stack frame to maintain data integrity 4. no self-modifying code Recursion recursive code must be reentrant recursive reentrant but reentrant recursive e.g. calculating 3! using recursion main move.w number,D0 pass the number jsr fact start recursive rtn move.w D0,result store the factorial stop #$2700 number dc.w 3 result ds.w 1 fact link A6,#-2 Stack structure move.w D0,-2(A6) subq.w #1,D0 bne push move.w -2(A6),D0 bra return push jsr fact mulu -2(A6),D0 return unlk A6 rts end main SP ->/////// A much more complex example: X: array [0..30] of words Y: longword Z, ALPHA, N: byte call order is S/R demo(X, Y, Z, ALPHA, N ) N is passed/returned by value, all others are passed by reference demo(X[w:31], Y[l], Z[b], ALPHA[b], N[b]) main CLR.W D2 zero entire word MOVE.B N,D2 N to low byte MOVE.W D2,-(SP) N on stack PEA ALPHA push arguments PEA Z in reverse order PEA Y PEA X JSR demo call -
Shared Objects & Mutual Exclusion
Chapter 4 Shared Objects & Mutual Exclusion Shared Objects & Concepts: process interference. Mutual Exclusion mutual exclusion and locks. Models: model checking for interference modelling mutual exclusion Practice: thread interference in shared Java objects mutual exclusion in Java (synchronized objects/methods). 1 2 2015 Concurrency: shared objects & mutual exclusion ©Magee/Kramer 2nd Edition 2015 Concurrency: shared objects & mutual exclusion ©Magee/Kramer 2nd Edition A Concert Hall Booking System Concert Hall Booking System const False = 0 A central computer connected to remote terminals via communication links const True = 1 is used to automate seat reservations for a concert hall. range Bool = False..True To book a seat, a client chooses a free seat and the clerk enters the number SEAT = SEAT[False], of the chosen seat at the terminal and issues a ticket, if it is free. SEAT[reserved:Bool] = ( when (!reserved) reserve -> SEAT[True] A system is required which avoids double bookings of the same seat whilst | query[reserved] -> SEAT[reserved] allowing clients free choice of the available seats. | when (reserved) reserve -> ERROR //error of reserved twice Construct an abstract model of the system and demonstrate that your model does ). not permit double bookings. Like STOP, ERROR range Seats = 1..2 is a predefined FSP ||SEATS = (seat[Seats]:SEAT). local process (state), numbered -1 in the 3 equivalent LTS. 4 2015 Concurrency: shared objects & mutual exclusion ©Magee/Kramer 2nd Edition 2015 Concurrency: shared objects & mutual exclusion ©Magee/Kramer 2nd Edition Concert Hall Booking System Concert Hall Booking System – no interference? LOCK = (acquire -> release -> LOCK). TERMINAL = (choose[s:Seats] //lock for the booking system -> seat[s].query[reserved:Bool] -> if (!reserved) then TERMINAL = (choose[s:Seats] -> acquire (seat[s].reserve -> TERMINAL) -> seat[s].query[reserved:Bool] else -> if (!reserved) then TERMINAL (seat[s].reserve -> release-> TERMINAL) ). -
Actor-Based Concurrency by Srinivas Panchapakesan
Concurrency in Java and Actor- based concurrency using Scala By, Srinivas Panchapakesan Concurrency Concurrent computing is a form of computing in which programs are designed as collections of interacting computational processes that may be executed in parallel. Concurrent programs can be executed sequentially on a single processor by interleaving the execution steps of each computational process, or executed in parallel by assigning each computational process to one of a set of processors that may be close or distributed across a network. The main challenges in designing concurrent programs are ensuring the correct sequencing of the interactions or communications between different computational processes, and coordinating access to resources that are shared among processes. Advantages of Concurrency Almost every computer nowadays has several CPU's or several cores within one CPU. The ability to leverage theses multi-cores can be the key for a successful high-volume application. Increased application throughput - parallel execution of a concurrent program allows the number of tasks completed in certain time period to increase. High responsiveness for input/output-intensive applications mostly wait for input or output operations to complete. Concurrent programming allows the time that would be spent waiting to be used for another task. More appropriate program structure - some problems and problem domains are well-suited to representation as concurrent tasks or processes. Process vs Threads Process: A process runs independently and isolated of other processes. It cannot directly access shared data in other processes. The resources of the process are allocated to it via the operating system, e.g. memory and CPU time. Threads: Threads are so called lightweight processes which have their own call stack but an access shared data. -
Sec9on 6: Mutual Exclusion
Sec$on 6: Mutual Exclusion Michelle Ku5el [email protected] Toward sharing resources (memory) Have been studying parallel algorithms using fork- join – Lower span via parallel tasks Algorithms all had a very simple structure to avoid race condi$ons – Each thread had memory “only it accessed” • Example: array sub-range – On fork, “loaned” some of its memory to “forkee” and did not access that memory again un$l aer join on the “forkee” slide adapted from: Sophomoric Parallelism & 2 Concurrency, Lecture 4 Toward sharing resources (memory) Strategy won’t work well when: – Memory accessed by threads is overlapping or unpredictable – Threads are doing independent tasks needing access to same resources (rather than implemen$ng the same algorithm) slide adapted from: Sophomoric Parallelism & 3 Concurrency, Lecture 4 Race Condi$ons A race condi*on is a bug in a program where the output and/or result of the process is unexpectedly and cri$cally dependent on the relave sequence or $ming of other events. The idea is that the events race each other to influence the output first. Examples Mul$ple threads: 1. Processing different bank-account operaons – What if 2 threads change the same account at the same $me? 2. Using a shared cache (e.g., hashtable) of recent files – What if 2 threads insert the same file at the same $me? 3. Creang a pipeline (think assembly line) with a queue for handing work to next thread in sequence? – What if enqueuer and dequeuer adjust a circular array queue at the same $me? Sophomoric Parallelism & 5 Concurrency, Lecture 4 Concurrent -
Java Concurrency Framework by Sidartha Gracias
Java Concurrency Framework Sidartha Gracias Executive Summary • This is a beginners introduction to the java concurrency framework • Some familiarity with concurrent programs is assumed – However the presentation does go through a quick background on concurrency – So readers unfamiliar with concurrent programming should still get something out of this • The structure of the presentation is as follows – A brief history into concurrent programming is provided – Issues in concurrent programming are explored – The framework structure with all its major components are covered in some detail – Examples are provided for each major section to reinforce some of the major ideas Concurrency in Java - Overview • Java like most other languages supports concurrency through thread – The JVM creates the Initial thread, which begins execution from main – The main method can then spawn additional threads Thread Basics • All modern OS support the idea of processes – independently running programs that are isolated from each other • Thread can be thought of as light weight processes – Like processes they have independent program counters, call stacks etc – Unlike Processes they share main memory, file pointers and other process state – This means thread are easier for the OS to maintain and switch between – This also means we need to synchronize threads for access to shared resources Threads Continued… • So why use threads ? – Multi CPU systems: Most modern systems host multiple CPU’s, by splitting execution between them we can greatly speed up execution – Handling Asynchronous Events: Servers handle multiple clients. Processing each client is best done through a separate thread, because the Server blocks until a new message is received – UI or event driven Processing: event handlers that respond to user input are best handled through separate threads, this makes code easier to write and understand Synchronization Primitives in Java • How does the java language handle synchronization – Concurrent execution is supported through the Thread class. -
AN10381 Nesting of Interrupts in the LPC2000 Rev
AN10381 Nesting of interrupts in the LPC2000 Rev. 01 — 6 June 2005 Application note Document information Info Content Keywords nested, reentrant, interrupts, LPC2000 Abstract Details on reentrant interrupt handlers and code examples for the same is provided Philips Semiconductors AN10381 Nesting of interrupts in the LPC2000 Revision history Rev Date Description 01 20050606 Initial version Contact information For additional information, please visit: http://www.semiconductors.philips.com For sales office addresses, please send an email to: [email protected] © Koninklijke Philips Electronics N.V. 2005. All rights reserved. Application note Rev. 01 — 6 June 2005 2 of 14 Philips Semiconductors AN10381 Nesting of interrupts in the LPC2000 1. Introduction This application note provides code examples for effectively handling reentrant interrupt handlers in the LPC2000 devices. The following organization is been adopted for this application note. 1. Interrupt handling overview 2. Nesting of Interrupts 3. Code examples It is assumed for this application note, that the user is familiar with the ARM7TDMI-S architecture. Also, for code examples relating to simple interrupt handling using FIQ and IRQ, please refer to the AN10254_1 application note available online. All the code examples provided in this application note were built on the Keil MicroVision3 ARM compiler (an evaluation version of which is free for download at www.keil.com) 2. Interrupt handling overview 2.1 Interrupt levels in the ARM7 core The ARM7 processor supports two levels of interrupts: Interrupt Request (IRQ) and Fast Interrupt Request (FIQ). ARM recommends only one interrupt source to be classified as an FIQ. All other interrupt sources could be classified as IRQ’s and they could be programmed for reentrancy.