A Comparison of Blocking & Non-Blocking Synchronization
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Fast and Correct Load-Link/Store-Conditional Instruction Handling in DBT Systems
Fast and Correct Load-Link/Store-Conditional Instruction Handling in DBT Systems Abstract Atomic Read Memory Dynamic Binary Translation (DBT) requires the implemen- Operation tation of load-link/store-conditional (LL/SC) primitives for guest systems that rely on this form of synchronization. When Equals targeting e.g. x86 host systems, LL/SC guest instructions are YES NO typically emulated using atomic Compare-and-Swap (CAS) expected value? instructions on the host. Whilst this direct mapping is efficient, this approach is problematic due to subtle differences between Write new value LL/SC and CAS semantics. In this paper, we demonstrate that to memory this is a real problem, and we provide code examples that fail to execute correctly on QEMU and a commercial DBT system, Exchanged = true Exchanged = false which both use the CAS approach to LL/SC emulation. We then develop two novel and provably correct LL/SC emula- tion schemes: (1) A purely software based scheme, which uses the DBT system’s page translation cache for correctly se- Figure 1: The compare-and-swap instruction atomically reads lecting between fast, but unsynchronized, and slow, but fully from a memory address, and compares the current value synchronized memory accesses, and (2) a hardware acceler- with an expected value. If these values are equal, then a new ated scheme that leverages hardware transactional memory value is written to memory. The instruction indicates (usually (HTM) provided by the host. We have implemented these two through a return register or flag) whether or not the value was schemes in the Synopsys DesignWare® ARC® nSIM DBT successfully written. -
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. -
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. -
Synchronization: Locks
Last Class: Threads • Thread: a single execution stream within a process • Generalizes the idea of a process • Shared address space within a process • User level threads: user library, no kernel context switches • Kernel level threads: kernel support, parallelism • Same scheduling strategies can be used as for (single-threaded) processes – FCFS, RR, SJF, MLFQ, Lottery... Computer Science CS377: Operating Systems Lecture 5, page 1 Today: Synchronization • Synchronization – Mutual exclusion – Critical sections • Example: Too Much Milk • Locks • Synchronization primitives are required to ensure that only one thread executes in a critical section at a time. Computer Science CS377: Operating Systems Lecture 7, page 2 Recap: Synchronization •What kind of knowledge and mechanisms do we need to get independent processes to communicate and get a consistent view of the world (computer state)? •Example: Too Much Milk Time You Your roommate 3:00 Arrive home 3:05 Look in fridge, no milk 3:10 Leave for grocery store 3:15 Arrive home 3:20 Arrive at grocery store Look in fridge, no milk 3:25 Buy milk Leave for grocery store 3:35 Arrive home, put milk in fridge 3:45 Buy milk 3:50 Arrive home, put up milk 3:50 Oh no! Computer Science CS377: Operating Systems Lecture 7, page 3 Recap: Synchronization Terminology • Synchronization: use of atomic operations to ensure cooperation between threads • Mutual Exclusion: ensure that only one thread does a particular activity at a time and excludes other threads from doing it at that time • Critical Section: piece of code that only one thread can execute at a time • Lock: mechanism to prevent another process from doing something – Lock before entering a critical section, or before accessing shared data. -
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. -
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. -
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. -
INF4140 - Models of Concurrency Locks & Barriers, Lecture 2
Locks & barriers INF4140 - Models of concurrency Locks & barriers, lecture 2 Høsten 2015 31. 08. 2015 2 / 46 Practical Stuff Mandatory assignment 1 (“oblig”) Deadline: Friday September 25 at 18.00 Online delivery (Devilry): https://devilry.ifi.uio.no 3 / 46 Introduction Central to the course are general mechanisms and issues related to parallel programs Previously: await language and a simple version of the producer/consumer example Today Entry- and exit protocols to critical sections Protect reading and writing to shared variables Barriers Iterative algorithms: Processes must synchronize between each iteration Coordination using flags 4 / 46 Remember: await-example: Producer/Consumer 1 2 i n t buf, p := 0; c := 0; 3 4 process Producer { process Consumer { 5 i n t a [N ] ; . i n t b [N ] ; . 6 w h i l e ( p < N) { w h i l e ( c < N) { 7 < await ( p = c ) ; > < await ( p > c ) ; > 8 buf:=a[p]; b[c]:=buf; 9 p:=p+1; c:=c+1; 10 }} 11 }} Invariants An invariant holds in all states in all histories of the program. global invariant: c ≤ p ≤ c + 1 local (in the producer): 0 ≤ p ≤ N 5 / 46 Critical section Fundamental concept for concurrency Critical section: part of a program that is/needs to be “protected” against interference by other processes Execution under mutual exclusion Related to “atomicity” Main question today: How can we implement critical sections / conditional critical sections? Various solutions and properties/guarantees Using locks and low-level operations SW-only solutions? HW or OS support? Active waiting (later semaphores and passive waiting) 6 / 46 Access to Critical Section (CS) Several processes compete for access to a shared resource Only one process can have access at a time: “mutual exclusion” (mutex) Possible examples: Execution of bank transactions Access to a printer or other resources .. -
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. -
Mastering Concurrent Computing Through Sequential Thinking
review articles DOI:10.1145/3363823 we do not have good tools to build ef- A 50-year history of concurrency. ficient, scalable, and reliable concur- rent systems. BY SERGIO RAJSBAUM AND MICHEL RAYNAL Concurrency was once a specialized discipline for experts, but today the chal- lenge is for the entire information tech- nology community because of two dis- ruptive phenomena: the development of Mastering networking communications, and the end of the ability to increase processors speed at an exponential rate. Increases in performance come through concur- Concurrent rency, as in multicore architectures. Concurrency is also critical to achieve fault-tolerant, distributed services, as in global databases, cloud computing, and Computing blockchain applications. Concurrent computing through sequen- tial thinking. Right from the start in the 1960s, the main way of dealing with con- through currency has been by reduction to se- quential reasoning. Transforming problems in the concurrent domain into simpler problems in the sequential Sequential domain, yields benefits for specifying, implementing, and verifying concur- rent programs. It is a two-sided strategy, together with a bridge connecting the Thinking two sides. First, a sequential specificationof an object (or service) that can be ac- key insights ˽ A main way of dealing with the enormous challenges of building concurrent systems is by reduction to sequential I must appeal to the patience of the wondering readers, thinking. Over more than 50 years, more sophisticated techniques have been suffering as I am from the sequential nature of human developed to build complex systems in communication. this way. 12 ˽ The strategy starts by designing —E.W.