Synchronization Key Concepts: Critical Sections, Mutual Exclusion, Test-And-Set, Spinlocks, Blocking and Blocking Locks, Semaphores, Condition Variables, Deadlocks
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Synchronization Spinlocks - Semaphores
CS 4410 Operating Systems Synchronization Spinlocks - Semaphores Summer 2013 Cornell University 1 Today ● How can I synchronize the execution of multiple threads of the same process? ● Example ● Race condition ● Critical-Section Problem ● Spinlocks ● Semaphors ● Usage 2 Problem Context ● Multiple threads of the same process have: ● Private registers and stack memory ● Shared access to the remainder of the process “state” ● Preemptive CPU Scheduling: ● The execution of a thread is interrupted unexpectedly. ● Multiple cores executing multiple threads of the same process. 3 Share Counting ● Mr Skroutz wants to count his $1-bills. ● Initially, he uses one thread that increases a variable bills_counter for every $1-bill. ● Then he thought to accelerate the counting by using two threads and keeping the variable bills_counter shared. 4 Share Counting bills_counter = 0 ● Thread A ● Thread B while (machine_A_has_bills) while (machine_B_has_bills) bills_counter++ bills_counter++ print bills_counter ● What it might go wrong? 5 Share Counting ● Thread A ● Thread B r1 = bills_counter r2 = bills_counter r1 = r1 +1 r2 = r2 +1 bills_counter = r1 bills_counter = r2 ● If bills_counter = 42, what are its possible values after the execution of one A/B loop ? 6 Shared counters ● One possible result: everything works! ● Another possible result: lost update! ● Called a “race condition”. 7 Race conditions ● Def: a timing dependent error involving shared state ● It depends on how threads are scheduled. ● Hard to detect 8 Critical-Section Problem bills_counter = 0 ● Thread A ● Thread B while (my_machine_has_bills) while (my_machine_has_bills) – enter critical section – enter critical section bills_counter++ bills_counter++ – exit critical section – exit critical section print bills_counter 9 Critical-Section Problem ● The solution should ● enter section satisfy: ● critical section ● Mutual exclusion ● exit section ● Progress ● remainder section ● Bounded waiting 10 General Solution ● LOCK ● A process must acquire a lock to enter a critical section. -
Chapter 1. Origins of Mac OS X
1 Chapter 1. Origins of Mac OS X "Most ideas come from previous ideas." Alan Curtis Kay The Mac OS X operating system represents a rather successful coming together of paradigms, ideologies, and technologies that have often resisted each other in the past. A good example is the cordial relationship that exists between the command-line and graphical interfaces in Mac OS X. The system is a result of the trials and tribulations of Apple and NeXT, as well as their user and developer communities. Mac OS X exemplifies how a capable system can result from the direct or indirect efforts of corporations, academic and research communities, the Open Source and Free Software movements, and, of course, individuals. Apple has been around since 1976, and many accounts of its history have been told. If the story of Apple as a company is fascinating, so is the technical history of Apple's operating systems. In this chapter,[1] we will trace the history of Mac OS X, discussing several technologies whose confluence eventually led to the modern-day Apple operating system. [1] This book's accompanying web site (www.osxbook.com) provides a more detailed technical history of all of Apple's operating systems. 1 2 2 1 1.1. Apple's Quest for the[2] Operating System [2] Whereas the word "the" is used here to designate prominence and desirability, it is an interesting coincidence that "THE" was the name of a multiprogramming system described by Edsger W. Dijkstra in a 1968 paper. It was March 1988. The Macintosh had been around for four years. -
The Deadlock Problem
The deadlock problem More deadlocks mutex_t m1, m2; Same problem with condition variables void p1 (void *ignored) { • lock (m1); - Suppose resource 1 managed by c1, resource 2 by c2 lock (m2); - A has 1, waits on 2, B has 2, waits on 1 /* critical section */ c c unlock (m2); Or have combined mutex/condition variable unlock (m1); • } deadlock: - lock (a); lock (b); while (!ready) wait (b, c); void p2 (void *ignored) { unlock (b); unlock (a); lock (m2); - lock (a); lock (b); ready = true; signal (c); lock (m1); unlock (b); unlock (a); /* critical section */ unlock (m1); One lesson: Dangerous to hold locks when crossing unlock (m2); • } abstraction barriers! This program can cease to make progress – how? - I.e., lock (a) then call function that uses condition variable • Can you have deadlock w/o mutexes? • 1/15 2/15 Deadlocks w/o computers Deadlock conditions 1. Limited access (mutual exclusion): - Resource can only be shared with finite users. 2. No preemption: - once resource granted, cannot be taken away. Real issue is resources & how required • 3. Multiple independent requests (hold and wait): E.g., bridge only allows traffic in one direction - don’t ask all at once (wait for next resource while holding • - Each section of a bridge can be viewed as a resource. current one) - If a deadlock occurs, it can be resolved if one car backs up 4. Circularity in graph of requests (preempt resources and rollback). All of 1–4 necessary for deadlock to occur - Several cars may have to be backed up if a deadlock occurs. • Two approaches to dealing with deadlock: - Starvation is possible. -
Fair K Mutual Exclusion Algorithm for Peer to Peer Systems ∗
Fair K Mutual Exclusion Algorithm for Peer To Peer Systems ∗ Vijay Anand Reddy, Prateek Mittal, and Indranil Gupta University of Illinois, Urbana Champaign, USA {vkortho2, mittal2, indy}@uiuc.edu Abstract is when multiple clients are simultaneously downloading a large multimedia file, e.g., [3, 12]. Finally applications k-mutual exclusion is an important problem for resource- where a service has limited computational resources will intensive peer-to-peer applications ranging from aggrega- also benefit from a k mutual exclusion primitive, preventing tion to file downloads. In order to be practically useful, scenarios where all the nodes of the p2p system simultane- k-mutual exclusion algorithms not only need to be safe and ously overwhelm the server. live, but they also need to be fair across hosts. We pro- The k mutual exclusion problem involves a group of pro- pose a new solution to the k-mutual exclusion problem that cesses, each of which intermittently requires access to an provides a notion of time-based fairness. Specifically, our identical resource called the critical section (CS). A k mu- algorithm attempts to minimize the spread of access time tual exclusion algorithm must satisfy both safety and live- for the critical resource. While a client’s access time is ness. Safety means that at most k processes, 1 ≤ k ≤ n, the time between it requesting and accessing the resource, may be in the CS at any given time. Liveness means that the spread is defined as a system-wide metric that measures every request for critical section access is satisfied in finite some notion of the variance of access times across a homo- time. -
CS350 – Operating Systems
Outline 1 Processes and Threads 2 Synchronization 3 Memory Management 1 / 45 Processes • A process is an instance of a program running • Modern OSes run multiple processes simultaneously • Very early OSes only ran one process at a time • Examples (can all run simultaneously): - emacs – text editor - firefox – web browser • Non-examples (implemented as one process): - Multiple firefox windows or emacs frames (still one process) • Why processes? - Simplicity of programming - Speed: Higher throughput, lower latency 2 / 45 A process’s view of the world • Each process has own view of machine - Its own address space - Its own open files - Its own virtual CPU (through preemptive multitasking) • *(char *)0xc000 dierent in P1 & P2 3 / 45 System Calls • Systems calls are the interface between processes and the kernel • A process invokes a system call to request operating system services • fork(), waitpid(), open(), close() • Note: Signals are another common mechanism to allow the kernel to notify the application of an important event (e.g., Ctrl-C) - Signals are like interrupts/exceptions for application code 4 / 45 System Call Soware Stack Application 1 5 Syscall Library unprivileged code 4 2 privileged 3 code Kernel 5 / 45 Kernel Privilege • Hardware provides two or more privilege levels (or protection rings) • Kernel code runs at a higher privilege level than applications • Typically called Kernel Mode vs. User Mode • Code running in kernel mode gains access to certain CPU features - Accessing restricted features (e.g. Co-processor 0) - Disabling interrupts, setup interrupt handlers - Modifying the TLB (for virtual memory management) • Allows the kernel to isolate processes from one another and from the kernel - Processes cannot read/write kernel memory - Processes cannot directly call kernel functions 6 / 45 How System Calls Work • The kernel only runs through well defined entry points • Interrupts - Interrupts are generated by devices to signal needing attention - E.g. -
The Challenges of Hardware Synthesis from C-Like Languages
The Challenges of Hardware Synthesis from C-like Languages Stephen A. Edwards∗ Department of Computer Science Columbia University, New York Abstract most successful C-like languages, in fact, bear little syntactic or semantic resemblance to C, effectively forcing users to learn The relentless increase in the complexity of integrated circuits a new language anyway. As a result, techniques for synthesiz- we can fabricate imposes a continuing need for ways to de- ing hardware from C either generate inefficient hardware or scribe complex hardware succinctly. Because of their ubiquity propose a language that merely adopts part of C syntax. and flexibility, many have proposed to use the C and C++ lan- For space reasons, this paper is focused purely on the use of guages as specification languages for digital hardware. Yet, C-like languages for synthesis. I deliberately omit discussion tools based on this idea have seen little commercial interest. of other important uses of a design language, such as validation In this paper, I argue that C/C++ is a poor choice for specify- and algorithm exploration. C-like languages are much more ing hardware for synthesis and suggest a set of criteria that the compelling for these tasks, and one in particular (SystemC) is next successful hardware description language should have. now widely used, as are many ad hoc variants. 1 Introduction 2 A Short History of C Familiarity is the main reason C-like languages have been pro- Dennis Ritchie developed C in the early 1970 [18] based on posed for hardware synthesis. Synthesize hardware from C, experience with Ken Thompson’s B language, which had itself proponents claim, and we will effectively turn every C pro- evolved from Martin Richards’ BCPL [17]. -
4. Process Synchronization
Lecture Notes for CS347: Operating Systems Mythili Vutukuru, Department of Computer Science and Engineering, IIT Bombay 4. Process Synchronization 4.1 Race conditions and Locks • Multiprogramming and concurrency bring in the problem of race conditions, where multiple processes executing concurrently on shared data may leave the shared data in an undesirable, inconsistent state due to concurrent execution. Note that race conditions can happen even on a single processor system, if processes are context switched out by the scheduler, or are inter- rupted otherwise, while updating shared data structures. • Consider a simple example of two threads of a process incrementing a shared variable. Now, if the increments happen in parallel, it is possible that the threads will overwrite each other’s result, and the counter will not be incremented twice as expected. That is, a line of code that increments a variable is not atomic, and can be executed concurrently by different threads. • Pieces of code that must be accessed in a mutually exclusive atomic manner by the contending threads are referred to as critical sections. Critical sections must be protected with locks to guarantee the property of mutual exclusion. The code to update a shared counter is a simple example of a critical section. Code that adds a new node to a linked list is another example. A critical section performs a certain operation on a shared data structure, that may temporar- ily leave the data structure in an inconsistent state in the middle of the operation. Therefore, in order to maintain consistency and preserve the invariants of shared data structures, critical sections must always execute in a mutually exclusive fashion. -
Lock (TCB) Block (TCB)
Concurrency and Synchronizaon Mo0vaon • Operang systems (and applicaon programs) o<en need to be able to handle mul0ple things happening at the same 0me – Process execu0on, interrupts, background tasks, system maintenance • Humans are not very good at keeping track of mul0ple things happening simultaneously • Threads and synchronizaon are an abstrac0on to help bridge this gap Why Concurrency? • Servers – Mul0ple connec0ons handled simultaneously • Parallel programs – To achieve beGer performance • Programs with user interfaces – To achieve user responsiveness while doing computaon • Network and disk bound programs – To hide network/disk latency Definions • A thread is a single execu0on sequence that represents a separately schedulable task – Single execu0on sequence: familiar programming model – Separately schedulable: OS can run or suspend a thread at any 0me • Protec0on is an orthogonal concept – Can have one or many threads per protec0on domain Threads in the Kernel and at User-Level • Mul0-process kernel – Mul0ple single-threaded processes – System calls access shared kernel data structures • Mul0-threaded kernel – mul0ple threads, sharing kernel data structures, capable of using privileged instruc0ons – UNIX daemon processes -> mul0-threaded kernel • Mul0ple mul0-threaded user processes – Each with mul0ple threads, sharing same data structures, isolated from other user processes – Plus a mul0-threaded kernel Thread Abstrac0on • Infinite number of processors • Threads execute with variable speed – Programs must be designed to work with any schedule Programmer Abstraction Physical Reality Threads Processors 1 2 3 4 5 1 2 Running Ready Threads Threads Queson Why do threads execute at variable speed? Programmer vs. Processor View Programmers Possible Possible Possible View Execution Execution Execution #1 #2 #3 . -
Synchronously Waiting on Asynchronous Operations
Document No. P1171R0 Date 2018-10-07 Reply To Lewis Baker <[email protected]> Audience SG1, LEWG Synchronously waiting on asynchronous operations Overview The paper P1056R0 introduces a new std::experimental::task<T> type. This type represents an asynchronous operation that requires applying operator co_await to the task retrieve the result. The task<T> type is an instance of the more general concept of Awaitable types. The limitation of Awaitable types is that they can only be co_awaited from within a coroutine. For example, from the body of another task<T> coroutine. However, then you still end up with another Awaitable type that must be co_awaited within another coroutine. This presents a problem of how to start executing the first task and wait for it to complete. task<int> f(); task<int> g() { // Call to f() returns a not-yet-started task. // Applying operator co_await() to the task starts its execution // and suspends the current coroutine until it completes. int a = co_await f(); co_return a + 1; } int main() { task<int> t = g(); // But how do we start executing g() and waiting for it to complete // when outside of a coroutine context, such as in main()? int x = ???; return x; } This paper proposes a new function, sync_wait(), that will allow a caller to pass an arbitrary Awaitable type into the function. The function will co_await the passed Awaitable object on the current thread and then block waiting for that co_await operation to complete; either synchronously on the current thread, or asynchronously on another thread. When the operation completes, the result is captured on whichever thread the operation completed on. -
Kernel and Locking
Kernel and Locking Luca Abeni [email protected] Monolithic Kernels • Traditional Unix-like structure • Protection: distinction between Kernel (running in KS) and User Applications (running in US) • The kernel behaves as a single-threaded program • One single execution flow in KS at each time • Simplify consistency of internal kernel structures • Execution enters the kernel in two ways: • Coming from upside (system calls) • Coming from below (hardware interrupts) Kernel Programming Kernel Locking Single-Threaded Kernels • Only one single execution flow (thread) can execute in the kernel • It is not possible to execute more than 1 system call at time • Non-preemptable system calls • In SMP systems, syscalls are critical sections (execute in mutual exclusion) • Interrupt handlers execute in the context of the interrupted task Kernel Programming Kernel Locking Bottom Halves • Interrupt handlers split in two parts • Short and fast ISR • “Soft IRQ handler” • Soft IRQ hanlder: deferred handler • Traditionally known ass Bottom Half (BH) • AKA Deferred Procedure Call - DPC - in Windows • Linux: distinction between “traditional” BHs and Soft IRQ handlers Kernel Programming Kernel Locking Synchronizing System Calls and BHs • Synchronization with ISRs by disabling interrupts • Synchronization with BHs: is almost automatic • BHs execute atomically (a BH cannot interrupt another BH) • BHs execute at the end of the system call, before invoking the scheduler for returning to US • Easy synchronization, but large non-preemptable sections! • Achieved -
Lock-Free Programming
Lock-Free Programming Geoff Langdale L31_Lockfree 1 Desynchronization ● This is an interesting topic ● This will (may?) become even more relevant with near ubiquitous multi-processing ● Still: please don’t rewrite any Project 3s! L31_Lockfree 2 Synchronization ● We received notification via the web form that one group has passed the P3/P4 test suite. Congratulations! ● We will be releasing a version of the fork-wait bomb which doesn't make as many assumptions about task id's. – Please look for it today and let us know right away if it causes any trouble for you. ● Personal and group disk quotas have been grown in order to reduce the number of people running out over the weekend – if you try hard enough you'll still be able to do it. L31_Lockfree 3 Outline ● Problems with locking ● Definition of Lock-free programming ● Examples of Lock-free programming ● Linux OS uses of Lock-free data structures ● Miscellanea (higher-level constructs, ‘wait-freedom’) ● Conclusion L31_Lockfree 4 Problems with Locking ● This list is more or less contentious, not equally relevant to all locking situations: – Deadlock – Priority Inversion – Convoying – “Async-signal-safety” – Kill-tolerant availability – Pre-emption tolerance – Overall performance L31_Lockfree 5 Problems with Locking 2 ● Deadlock – Processes that cannot proceed because they are waiting for resources that are held by processes that are waiting for… ● Priority inversion – Low-priority processes hold a lock required by a higher- priority process – Priority inheritance a possible solution L31_Lockfree -
Download Distributed Systems Free Ebook
DISTRIBUTED SYSTEMS DOWNLOAD FREE BOOK Maarten van Steen, Andrew S Tanenbaum | 596 pages | 01 Feb 2017 | Createspace Independent Publishing Platform | 9781543057386 | English | United States Distributed Systems - The Complete Guide The hope is that together, the system can maximize resources and information while preventing failures, as if one system fails, it won't affect the availability of the service. Banker's algorithm Dijkstra's algorithm DJP algorithm Prim's algorithm Dijkstra-Scholten algorithm Dekker's algorithm generalization Smoothsort Shunting-yard algorithm Distributed Systems marking algorithm Concurrent algorithms Distributed Systems algorithms Deadlock prevention algorithms Mutual exclusion algorithms Self-stabilizing Distributed Systems. Learn to code for free. For the first time computers would be able to send messages to other systems with a local IP address. The messages passed between machines contain forms of data that the systems want to share like databases, objects, and Distributed Systems. Also known as distributed computing and distributed databases, a distributed system is a collection of independent components located on different machines that share messages with each other in order to achieve common goals. To prevent infinite loops, running the code requires some amount of Ether. As mentioned in many places, one of which this great articleyou cannot have consistency and availability without partition tolerance. Because it works in batches jobs a problem arises where if your job fails — Distributed Systems need to restart the whole thing. While in a voting system an attacker need only add nodes to the network which is Distributed Systems, as free access to the network is a design targetin a CPU power based scheme an attacker faces a physical limitation: getting access to more and more powerful hardware.