CSC 553 Operating Systems Multiple Processes
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
An Introduction to Linux IPC
An introduction to Linux IPC Michael Kerrisk © 2013 linux.conf.au 2013 http://man7.org/ Canberra, Australia [email protected] 2013-01-30 http://lwn.net/ [email protected] man7 .org 1 Goal ● Limited time! ● Get a flavor of main IPC methods man7 .org 2 Me ● Programming on UNIX & Linux since 1987 ● Linux man-pages maintainer ● http://www.kernel.org/doc/man-pages/ ● Kernel + glibc API ● Author of: Further info: http://man7.org/tlpi/ man7 .org 3 You ● Can read a bit of C ● Have a passing familiarity with common syscalls ● fork(), open(), read(), write() man7 .org 4 There’s a lot of IPC ● Pipes ● Shared memory mappings ● FIFOs ● File vs Anonymous ● Cross-memory attach ● Pseudoterminals ● proc_vm_readv() / proc_vm_writev() ● Sockets ● Signals ● Stream vs Datagram (vs Seq. packet) ● Standard, Realtime ● UNIX vs Internet domain ● Eventfd ● POSIX message queues ● Futexes ● POSIX shared memory ● Record locks ● ● POSIX semaphores File locks ● ● Named, Unnamed Mutexes ● System V message queues ● Condition variables ● System V shared memory ● Barriers ● ● System V semaphores Read-write locks man7 .org 5 It helps to classify ● Pipes ● Shared memory mappings ● FIFOs ● File vs Anonymous ● Cross-memory attach ● Pseudoterminals ● proc_vm_readv() / proc_vm_writev() ● Sockets ● Signals ● Stream vs Datagram (vs Seq. packet) ● Standard, Realtime ● UNIX vs Internet domain ● Eventfd ● POSIX message queues ● Futexes ● POSIX shared memory ● Record locks ● ● POSIX semaphores File locks ● ● Named, Unnamed Mutexes ● System V message queues ● Condition variables ● System V shared memory ● Barriers ● ● System V semaphores Read-write locks man7 .org 6 It helps to classify ● Pipes ● Shared memory mappings ● FIFOs ● File vs Anonymous ● Cross-memoryn attach ● Pseudoterminals tio a ● proc_vm_readv() / proc_vm_writev() ● Sockets ic n ● Signals ● Stream vs Datagram (vs uSeq. -
Introduction to Multi-Threading and Vectorization Matti Kortelainen Larsoft Workshop 2019 25 June 2019 Outline
Introduction to multi-threading and vectorization Matti Kortelainen LArSoft Workshop 2019 25 June 2019 Outline Broad introductory overview: • Why multithread? • What is a thread? • Some threading models – std::thread – OpenMP (fork-join) – Intel Threading Building Blocks (TBB) (tasks) • Race condition, critical region, mutual exclusion, deadlock • Vectorization (SIMD) 2 6/25/19 Matti Kortelainen | Introduction to multi-threading and vectorization Motivations for multithreading Image courtesy of K. Rupp 3 6/25/19 Matti Kortelainen | Introduction to multi-threading and vectorization Motivations for multithreading • One process on a node: speedups from parallelizing parts of the programs – Any problem can get speedup if the threads can cooperate on • same core (sharing L1 cache) • L2 cache (may be shared among small number of cores) • Fully loaded node: save memory and other resources – Threads can share objects -> N threads can use significantly less memory than N processes • If smallest chunk of data is so big that only one fits in memory at a time, is there any other option? 4 6/25/19 Matti Kortelainen | Introduction to multi-threading and vectorization What is a (software) thread? (in POSIX/Linux) • “Smallest sequence of programmed instructions that can be managed independently by a scheduler” [Wikipedia] • A thread has its own – Program counter – Registers – Stack – Thread-local memory (better to avoid in general) • Threads of a process share everything else, e.g. – Program code, constants – Heap memory – Network connections – File handles -
Multithreading Design Patterns and Thread-Safe Data Structures
Lecture 12: Multithreading Design Patterns and Thread-Safe Data Structures Principles of Computer Systems Autumn 2019 Stanford University Computer Science Department Lecturer: Chris Gregg Philip Levis PDF of this presentation 1 Review from Last Week We now have three distinct ways to coordinate between threads: mutex: mutual exclusion (lock), used to enforce critical sections and atomicity condition_variable: way for threads to coordinate and signal when a variable has changed (integrates a lock for the variable) semaphore: a generalization of a lock, where there can be n threads operating in parallel (a lock is a semaphore with n=1) 2 Mutual Exclusion (mutex) A mutex is a simple lock that is shared between threads, used to protect critical regions of code or shared data structures. mutex m; mutex.lock() mutex.unlock() A mutex is often called a lock: the terms are mostly interchangeable When a thread attempts to lock a mutex: Currently unlocked: the thread takes the lock, and continues executing Currently locked: the thread blocks until the lock is released by the current lock- holder, at which point it attempts to take the lock again (and could compete with other waiting threads). Only the current lock-holder is allowed to unlock a mutex Deadlock can occur when threads form a circular wait on mutexes (e.g. dining philosophers) Places we've seen an operating system use mutexes for us: All file system operation (what if two programs try to write at the same time? create the same file?) Process table (what if two programs call fork() at the same time?) 3 lock_guard<mutex> The lock_guard<mutex> is very simple: it obtains the lock in its constructor, and releases the lock in its destructor. -
Deadlock: Why Does It Happen? CS 537 Andrea C
UNIVERSITY of WISCONSIN-MADISON Computer Sciences Department Deadlock: Why does it happen? CS 537 Andrea C. Arpaci-Dusseau Introduction to Operating Systems Remzi H. Arpaci-Dusseau Informal: Every entity is waiting for resource held by another entity; none release until it gets what it is Deadlock waiting for Questions answered in this lecture: What are the four necessary conditions for deadlock? How can deadlock be prevented? How can deadlock be avoided? How can deadlock be detected and recovered from? Deadlock Example Deadlock Example Two threads access two shared variables, A and B int A, B; Variable A is protected by lock x, variable B by lock y lock_t x, y; How to add lock and unlock statements? Thread 1 Thread 2 int A, B; lock(x); lock(y); A += 10; B += 10; lock(y); lock(x); Thread 1 Thread 2 B += 20; A += 20; A += 10; B += 10; A += B; A += B; B += 20; A += 20; unlock(y); unlock(x); A += B; A += B; A += 30; B += 30; A += 30; B += 30; unlock(x); unlock(y); What can go wrong?? 1 Representing Deadlock Conditions for Deadlock Two common ways of representing deadlock Mutual exclusion • Vertices: • Resource can not be shared – Threads (or processes) in system – Resources (anything of value, including locks and semaphores) • Requests are delayed until resource is released • Edges: Indicate thread is waiting for the other Hold-and-wait Wait-For Graph Resource-Allocation Graph • Thread holds one resource while waits for another No preemption “waiting for” wants y held by • Resources are released voluntarily after completion T1 T2 T1 T2 Circular -
The Dining Philosophers Problem Cache Memory
The Dining Philosophers Problem Cache Memory 254 The dining philosophers problem: definition It is an artificial problem widely used to illustrate the problems linked to resource sharing in concurrent programming. The problem is usually described as follows. • A given number of philosopher are seated at a round table. • Each of the philosophers shares his time between two activities: thinking and eating. • To think, a philosopher does not need any resources; to eat he needs two pieces of silverware. 255 • However, the table is set in a very peculiar way: between every pair of adjacent plates, there is only one fork. • A philosopher being clumsy, he needs two forks to eat: the one on his right and the one on his left. • It is thus impossible for a philosopher to eat at the same time as one of his neighbors: the forks are a shared resource for which the philosophers are competing. • The problem is to organize access to these shared resources in such a way that everything proceeds smoothly. 256 The dining philosophers problem: illustration f4 P4 f0 P3 f3 P0 P2 P1 f1 f2 257 The dining philosophers problem: a first solution • This first solution uses a semaphore to model each fork. • Taking a fork is then done by executing a operation wait on the semaphore, which suspends the process if the fork is not available. • Freeing a fork is naturally done with a signal operation. 258 /* Definitions and global initializations */ #define N = ? /* number of philosophers */ semaphore fork[N]; /* semaphores modeling the forks */ int j; for (j=0, j < N, j++) fork[j]=1; Each philosopher (0 to N-1) corresponds to a process executing the following procedure, where i is the number of the philosopher. -
Semaphores Semaphores (Basic) Semaphore General Vs. Binary
Concurrent Programming (RIO) 20.1.2012 Lesson 6 Synchronization with HW support • Disable interrupts – Good for short time wait, not good for long time wait – Not good for multiprocessors Semaphores • Interrupts are disabled only in the processor used • Test-and-set instruction (etc) Ch 6 [BenA 06] – Good for short time wait, not good for long time wait – Nor so good in single processor system • May reserve CPU, which is needed by the process holding the lock – Waiting is usually “busy wait” in a loop Semaphores • Good for mutex, not so good for general synchronization – E.g., “wait until process P34 has reached point X” Producer-Consumer Problem – No support for long time wait (in suspended state) Semaphores in C--, Java, • Barrier wait in HW in some multicore architectures – Stop execution until all cores reached barrier_waitinstruction Linux, Minix – No busy wait, because execution pipeline just stops – Not to be confused with barrier_wait thread operation 20.1.2012 Copyright Teemu Kerola 2012 1 20.1.2012 Copyright Teemu Kerola 2012 2 Semaphores (Basic) Semaphore semaphore S public create initial value integer value semafori public P(S) S.value private S.V Edsger W. Dijkstra V(S) http://en.wikipedia.org/wiki/THE_operating_system public private S.list S.L • Dijkstra, 1965, THE operating system queue of waiting processes • Protected variable, abstract data type (object) • P(S) WAIT(S), Down(S) – Allows for concurrency solutions if used properly – If value > 0, deduct 1 and proceed • Atomic operations – o/w, wait suspended in list (queue?) until released – Create (SemaName, InitValue) – P, down, wait, take, pend, • V(S) SIGNAL(S), Up(S) passeren, proberen, try, prolaad, try to decrease – If someone in queue, release one (first?) of them – V, up, signal, release, post, – o/w, increase value by one vrijgeven, verlagen, verhoog, increase 20.1.2012 Copyright Teemu Kerola 2012 3 20.1.2012 Copyright Teemu Kerola 2012 4 General vs. -
Supervision 1: Semaphores, Generalised Producer-Consumer, and Priorities
Concurrent and Distributed Systems - 2015–2016 Supervision 1: Semaphores, generalised producer-consumer, and priorities Q0 Semaphores (a) Counting semaphores are initialised to a value — 0, 1, or some arbitrary n. For each case, list one situation in which that initialisation would make sense. (b) Write down two fragments of pseudo-code, to be run in two different threads, that experience deadlock as a result of poor use of mutual exclusion. (c) Deadlock is not limited to mutual exclusion; it can occur any time its preconditions (especially hold-and-wait, cyclic dependence) occur. Describe a situation in which two threads making use of semaphores for condition synchronisation (e.g., in producer-consumer) can deadlock. int buffer[N]; int in = 0, out = 0; spaces = new Semaphore(N); items = new Semaphore(0); guard = new Semaphore(1); // for mutual exclusion // producer threads while(true) { item = produce(); wait(spaces); wait(guard); buffer[in] = item; in = (in + 1) % N; signal(guard); signal(items); } // consumer threads while(true) { wait(items); wait(guard); item = buffer[out]; out =(out+1) % N; signal(guard); signal(spaces); consume(item); } Figure 1: Pseudo-code for a producer-consumer queue using semaphores. 1 (d) In Figure 1, items and spaces are used for condition synchronisation, and guard is used for mutual exclusion. Why will this implementation become unsafe in the presence of multiple consumer threads or multiple producer threads, if we remove guard? (e) Semaphores are introduced in part to improve efficiency under contention around critical sections by preferring blocking to spinning. Describe a situation in which this might not be the case; more generally, under what circumstances will semaphores hurt, rather than help, performance? (f) The implementation of semaphores themselves depends on two classes of operations: in- crement/decrement of an integer, and blocking/waking up threads. -
Q1. Multiple Producers and Consumers
CS39002: Operating Systems Lab. Assignment 5 Floating date: 29/2/2016 Due date: 14/3/2016 Q1. Multiple Producers and Consumers Problem Definition: You have to implement a system which ensures synchronisation in a producer-consumer scenario. You also have to demonstrate deadlock condition and provide solutions for avoiding deadlock. In this system a main process creates 5 producer processes and 5 consumer processes who share 2 resources (queues). The producer's job is to generate a piece of data, put it into the queue and repeat. At the same time, the consumer process consumes the data i.e., removes it from the queue. In the implementation, you are asked to ensure synchronization and mutual exclusion. For instance, the producer should be stopped if the buffer is full and that the consumer should be blocked if the buffer is empty. You also have to enforce mutual exclusion while the processes are trying to acquire the resources. Manager (manager.c): It is the main process that creates the producers and consumer processes (5 each). After that it periodically checks whether the system is in deadlock. Deadlock refers to a specific condition when two or more processes are each waiting for another to release a resource, or more than two processes are waiting for resources in a circular chain. Implementation : The manager process (manager.c) does the following : i. It creates a file matrix.txt which holds a matrix with 2 rows (number of resources) and 10 columns (ID of producer and consumer processes). Each entry (i, j) of that matrix can have three values: ● 0 => process i has not requested for queue j or released queue j ● 1 => process i requested for queue j ● 2 => process i acquired lock of queue j. -
Lesson-9: P and V SEMAPHORES
Inter-Process Communication and Synchronization of Processes, Threads and Tasks: Lesson-9: P and V SEMAPHORES Chapter-9 L9: "Embedded Systems - Architecture, Programming and Design", 2015 Raj Kamal, Publs.: McGraw-Hill Education 1 1. P and V SEMAPHORES Chapter-9 L9: "Embedded Systems - Architecture, Programming and Design", 2015 Raj Kamal, Publs.: McGraw-Hill Education 2 P and V semaphores • An efficient synchronisation mechanism • POSIX 1003.1.b, an IEEE standard. • POSIX─ for portable OS interfaces in Unix. • P and V semaphore ─ represents an integer in place of binary or unsigned integers Chapter-9 L9: "Embedded Systems - Architecture, Programming and Design", 2015 Raj Kamal, Publs.: McGraw-Hill Education 3 P and V semaphore Variables • The semaphore, apart from initialization, is accessed only through two standard atomic operations─ P and V • P (for wait operation)─ derived from a Dutch word ‘Proberen’, which means 'to test'. • V (for signal passing operation)─ derived from the word 'Verhogen' which means 'to increment'. Chapter-9 L9: "Embedded Systems - Architecture, Programming and Design", 2015 Raj Kamal, Publs.: McGraw-Hill Education 4 P and V Functions for Semaphore P semaphore function signals that the task requires a resource and if not available waits for it. V semaphore function signals which the task passes to the OS that the resource is now free for the other users. Chapter-9 L9: "Embedded Systems - Architecture, Programming and Design", 2015 Raj Kamal, Publs.: McGraw-Hill Education 5 P Function─ P (&Sem1) 1. /* Decrease the semaphore variable*/ sem_1 = sem_1 1; 2. /* If sem_1 is less than 0, send a message to OS by calling a function waitCallToOS. -
Shared Memory Programming: Threads, Semaphores, and Monitors
Shared Memory Programming: Threads, Semaphores, and Monitors CPS343 Parallel and High Performance Computing Spring 2020 CPS343 (Parallel and HPC) Shared Memory Programming: Threads, Semaphores, and MonitorsSpring 2020 1 / 47 Outline 1 Processes The Notion and Importance of Processes Process Creation and Termination Inter-process Communication and Coordination 2 Threads Need for Light Weight Processes Differences between Threads and Processes Implementing Threads 3 Mutual Exclusion and Semaphores Critical Sections Monitors CPS343 (Parallel and HPC) Shared Memory Programming: Threads, Semaphores, and MonitorsSpring 2020 2 / 47 Outline 1 Processes The Notion and Importance of Processes Process Creation and Termination Inter-process Communication and Coordination 2 Threads Need for Light Weight Processes Differences between Threads and Processes Implementing Threads 3 Mutual Exclusion and Semaphores Critical Sections Monitors CPS343 (Parallel and HPC) Shared Memory Programming: Threads, Semaphores, and MonitorsSpring 2020 3 / 47 What is a process? A process is a program in execution. At any given time, the status of a process includes: The code that it is executing (e.g. its text). Its data: The values of its static variables. The contents of its stack { which contains its local variables and procedure call/return history. The contents of the various CPU registers { particularly the program counter, which indicates what instruction the process is to execute next. Its state { is it currently able to continue execution, or must further execution wait until some event occurs (e.g. the completion of an IO operation it has requested)? CPS343 (Parallel and HPC) Shared Memory Programming: Threads, Semaphores, and MonitorsSpring 2020 4 / 47 What is a process? The chief task of an operating system is to manage a set of processes. -
Towards Gradually Typed Capabilities in the Pi-Calculus
Towards Gradually Typed Capabilities in the Pi-Calculus Matteo Cimini University of Massachusetts Lowell Lowell, MA, USA matteo [email protected] Gradual typing is an approach to integrating static and dynamic typing within the same language, and puts the programmer in control of which regions of code are type checked at compile-time and which are type checked at run-time. In this paper, we focus on the π-calculus equipped with types for the modeling of input-output capabilities of channels. We present our preliminary work towards a gradually typed version of this calculus. We present a type system, a cast insertion procedure that automatically inserts run-time checks, and an operational semantics of a π-calculus that handles casts on channels. Although we do not claim any theoretical results on our formulations, we demonstrate our calculus with an example and discuss our future plans. 1 Introduction This paper presents preliminary work on integrating dynamically typed features into a typed π-calculus. Pierce and Sangiorgi have defined a typed π-calculus in which channels can be assigned types that express input and output capabilities [16]. Channels can be declared to be input-only, output-only, or that can be used for both input and output operations. As a consequence, this type system can detect unintended or malicious channel misuses at compile-time. The static typing nature of the type system prevents the modeling of scenarios in which the input- output discipline of a channel is discovered at run-time. In these scenarios, such a discipline must be enforced with run-time type checks in the style of dynamic typing. -
Deadlock-Free Oblivious Routing for Arbitrary Topologies
Deadlock-Free Oblivious Routing for Arbitrary Topologies Jens Domke Torsten Hoefler Wolfgang E. Nagel Center for Information Services and Blue Waters Directorate Center for Information Services and High Performance Computing National Center for Supercomputing Applications High Performance Computing Technische Universitat¨ Dresden University of Illinois at Urbana-Champaign Technische Universitat¨ Dresden Dresden, Germany Urbana, IL 61801, USA Dresden, Germany [email protected] [email protected] [email protected] Abstract—Efficient deadlock-free routing strategies are cru- network performance without inclusion of the routing al- cial to the performance of large-scale computing systems. There gorithm or the application communication pattern. In reg- are many methods but it remains a challenge to achieve lowest ular operation these values can hardly be achieved due latency and highest bandwidth for irregular or unstructured high-performance networks. We investigate a novel routing to network congestion. The largest gap between real and strategy based on the single-source-shortest-path routing al- idealized performance is often in bisection bandwidth which gorithm and extend it to use virtual channels to guarantee by its definition only considers the topology. The effective deadlock-freedom. We show that this algorithm achieves min- bisection bandwidth [2] is the average bandwidth for routing imal latency and high bandwidth with only a low number messages between random perfect matchings of endpoints of virtual channels and can be implemented in practice. We demonstrate that the problem of finding the minimal number (also known as permutation routing) through the network of virtual channels needed to route a general network deadlock- and thus considers the routing algorithm.