DOCSLIB.ORG

Using Compile-Time Reflection for Object Checkpointing 1

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Using Compile-Time Reflection for Object Checkpointing 1 Using Compile-Time Reflection for Object Checkpointing 1 Marc-Olivier Killijian, Jean-Charles Fabre, Juan-Carlos Ruiz-Garcia LAAS-CNRS, 7 Avenue du Colonel Roche 31077 Toulouse cedex, France {killijian, fabre, ruiz}@laas.fr Abstract. This paper tackles the problem of checkpointing object oriented programs using a reflective approach. The objective of the technique and the corresponding tool is to provide checkpointing methods to application classes. In conventional object oriented fault-tolerant systems, the implementation of these methods to save and restore the state of objects is often delegated to the application programmer; the dependability of the system relies thus on his ability to implement these core functions. Our approach enable the automatic provision of these methods for classes that obey some programming restrictions. In a second step, we present an optimization of this technique using runtime reflection; the data checkpointed corresponding to the set of attributes that have been modified since the last checkpoint. Some preliminary results of the evaluation of these techniques and an overview of the CORBA system framework in which they are used is finally described. 1 Introduction The definition of application checkpoints is a major issue in the design and the implementation of dependable systems, especially for building fault tolerance strategies. Checkpointing the state of individual active objects is always needed for many replication strategies and mandatory for cloning a new replica during the reconfiguration of the system after a failure. The problem of checkpointing a distributed application involves complex algorithms to ensure the consistency of the distributed recovery state of the application. All these algorithms make the assumption that individual checkpoints of the application objects can be obtained easily. However, this is a strong assumption and, in practice, it is not so easy when complex active objects are considered. The available solutions either rely on very hardware or operating system dependent mechanisms or delegate this task to the application 1 This work has been partially supported by the European Esprit Project n° 20072, DEVA, by a contract with FRANCE TELECOM (ref. ST.CNET/DTL/ASR/97049/DT) and by a grant from CNRS (National Center for Scientific Research in France) in the framework of international agreements between CNRS and JSPS (Japan Society for the Promotion of Science). 1 / 20 programmer. These solutions have many drawbacks and recent approaches investigate the use of compiler-assisted checkpointing techniques [9, 15] . The proposed solution can be compared to the later and shows that compile-time reflection is a promising approach to tackle the problem of obtaining the state of individual objects. This state information is here obtained at a high level of abstraction and handled through the combined use of both compile-time and runtime reflection. The technique proposed here is part of the definition of a metaobject protocol for implementing fault tolerance in CORBA applications [8] , although its use is not restricted to this topic. Obtaining the state of an object is part of this MOP but is also useful for other aims, e.g. object migration in mobile systems or simply for load balancing. In this paper, we investigated this problem for object-oriented programs; the real question is what is the state of individual object oriented programs? This state is required to resume execution on a remote system. After a brief analysis of current approaches and an introduction to our solution (Section 2), we describe a new approach to the object state capture using compile-time reflection. Indeed, using class definitions and implementations at compile-time, we are able to generate automatically methods, such as SaveState and RestoreState, responsible for the capture and restoration of the state of objects of this class (Section 3). An optimization of this approach using runtime reflection is then proposed: thanks to runtime information, we are able to checkpoint only the attributes that have been modified since the last checkpoint (Section 4). A comparison of our approach with a conventional non-reflective compile-time solution illustrates both the performance efficiency and the coverage of the state capture (Section 5). Section 6 gives an overview of the system in which these mechanisms are presently used. 2 Problem Statement and Related Work The available techniques to obtain the state information of an object vary very much regarding the abstraction level where they apply and of course depend on the real information that is needed. The state information of an active object encompasses two kind of information, the internal state of the object (namely state variables) and the information in transit (invocation messages). We concentrate here on the internal state, the latter dealing with end-to-end communication protocols not described in this paper, see [5] . The internal state of an active object is mapped at a very low level to memory objects (segments, regions, etc.) which are handled either by the operating system or better by a middleware (the runtime layer for the application objects). Understanding the mapping implies diving into the operating system or the middleware to identify which memory objects hold the internal state of a given application object. This approach often leads to a customization of the software runtime layer in order to obtain such detailed information. This is a first drawback of this solution since off-the-shelf runtime layers cannot be used in this case. A second drawback of this solution is that it provides raw information concerning the state of an object. It is worth noting that such information is not appropriate to install and initialize a newly created object on a different site of the system for following reason: 2 / 20 1. Some data items are not significant on a different site since their value is very site dependent (e.g. pointers to objects, file descriptors, semaphore descriptors, etc.) 2. The semantics of state information variables must thus be interpreted in order to perform an appropriate initialization of such variables on a remote site. Indeed, some data items are related to internal objects within the middleware of the remote site; a raw copy of the memory objects is thus not consistent on the target site and some additional actions must be performed. These actions must create and initialize the corresponding internal objects within the runtime layer of the remote site. As soon as these actions complete and that the new instance is updated with the current state information, then the new object copy holds a consistent state from which the computation can continue. Such important observation indicates that semantic information regarding such data items is necessary to obtain a consistent checkpoint for the new object copy. Another approach consists in providing the user with libraries of functions [14] or classes [10, 11, 13] to deal with fault tolerance protocols and state information. In object oriented terms, the application classes must inherit from some base class in which the two methods SaveState and RestoreState are defined as virtual methods. This second approach is clearly not transparent for the user and relies on user’s skills to use the library functions or to implement the virtual methods correctly. This means that the implementation of both methods must be error-free. For instance, a wrong implementation of the SaveState function will lead the new copy to hold an inconsistent state from which the execution could not be restarted. This is a major drawback of such solutions. Moreover, since the implementation can be very difficult for very complex objects the probability of introducing software faults (bugs) in so doing is certainly very high. Another side effect of such solutions is that any modification (evolution) of the application object implementation must be consistently reported to the SaveState and RestoreState implementation. Because different application programmers can perform the long-term evolution of such application objects, a consistent implementation of these methods is not guaranteed during the lifetime of the application. Clearly, in the short or in the long term the whole distributed application will fail. It is worth noting that the definition and the implementation of such core functions must be tool assisted. Following this idea, some works have investigated the use of customized compilers to generate these functions automatically, e.g. [15] . More recently, the use of compile-time reflection was introduced to tackle this problem [7, 8] . In this type of solution, the identification of the internal state of application objects is very language dependent. This is however the only way to obtained detailed information about the internal state of application objects on off-the-shelf runtime systems. Any other solution would provide a coarse view of this information and make the interpretation of site-dependent objects very uncertain. A language independent solution would require the runtime system (the middleware, e.g. the ORB) to reify such detailed information, i.e. making the runtime system reflective. Both solutions rely on a reflective approach, the latter involving anyway a customization of the runtime system or the use of an appropriate reflective runtime system (only the Java runtime system provides type information using the java.lang.reflection package). 3 / 20 It is worth mentioning that pure object-oriented languages are easier to handle with this approach rather that hybrid languages such as C++. However, the experiments reported in this paper have been performed for C++ objects and the tool based on Open C++ [1] . This is why some programming conventions and restrictions have been considered in order to enforce a strong encapsulation principle and avoid programming statements that may lead to uncontrolled side effects to the object state. The necessary restrictions would have been very different using Java. We will comment on this point later, in section 4.3, but programming restrictions are not a real problem from our viewpoint.
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.
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • CSC 553 Operating Systems Multiple Processes
    CSC 553 Operating Systems Lecture 4 - Concurrency: Mutual Exclusion and Synchronization Multiple Processes • Operating System design is concerned with the management of processes and threads: • Multiprogramming • Multiprocessing • Distributed Processing Concurrency Arises in Three Different Contexts: • Multiple Applications – invented to allow processing time to be shared among active applications • Structured Applications – extension of modular design and structured programming • Operating System Structure – OS themselves implemented as a set of processes or threads Key Terms Related to Concurrency Principles of Concurrency • Interleaving and overlapping • can be viewed as examples of concurrent processing • both present the same problems • Uniprocessor – the relative speed of execution of processes cannot be predicted • depends on activities of other processes • the way the OS handles interrupts • scheduling policies of the OS Difficulties of Concurrency • Sharing of global resources • Difficult for the OS to manage the allocation of resources optimally • Difficult to locate programming errors as results are not deterministic and reproducible Race Condition • Occurs when multiple processes or threads read and write data items • The final result depends on the order of execution – the “loser” of the race is the process that updates last and will determine the final value of the variable Operating System Concerns • Design and management issues raised by the existence of concurrency: • The OS must: – be able to keep track of various processes
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • Software Transactional Memory with Interactions 3
    Software Transactional Memory with Interactions⋆ Extended Version Marino Miculan1 and Marco Peressotti2 1 University of Udine [email protected] 2 University of Southern Denmark [email protected] Abstract Software Transactional memory (STM) is an emerging ab- straction for concurrent programming alternative to lock-based synchron- izations. Most STM models admit only isolated transactions, which are not adequate in multithreaded programming where transactions need to interact via shared data before committing. To overcome this limitation, in this paper we present Open Transactional Memory (OTM), a pro- gramming abstraction supporting safe, data-driven interactions between composable memory transactions. This is achieved by relaxing isolation between transactions, still ensuring atomicity. This model allows for loosely-coupled interactions since transaction merging is driven only by accesses to shared data, with no need to specify participants beforehand. 1 Introduction Modern multicore architectures have emphasized the importance of abstractions supporting correct and scalable multi-threaded programming. In this model, threads can collaborate by interacting on shared data structures, such as tables, message queues, buffers, etc., whose access must be regulated to avoid inconsist- encies. Traditional lock-based mechanisms (like semaphores and monitors) are notoriously difficult and error-prone, as they easily lead to deadlocks, race con- ditions and priority inversions; moreover, they are not composable and hinder parallelism, thus reducing efficiency and scalability. Transactional memory (TM) has emerged as a promising abstraction to replace locks [5, 20]. The basic idea is to mark blocks of code as atomic; then, execution of each block will appear either as if it was executed sequentially and instantaneously at some unique point in time, or, if aborted, as if it did not execute at all.
    [Show full text]
  • Semaphores Cosc 450: Programming Paradigms 06
    CoSc 450: Programming Paradigms 06 Semaphores CoSc 450: Programming Paradigms 06 Semaphore Purpose: To prevent inefficient spin lock of the await statement. Idea: Instead of spinning, the process calls a method that puts it in a special queue of PCBs, the “blocked on semaphore” queue. 71447_CH08_Chapter08.qxd 1/28/09 12:27 AM Page 422 422 Chapter 8 Process Management The PCB contains additional information to help the operating system schedule the CPU. An example is a unique process identification number assigned by the system, labeled Process ID in Figure 8.18, that serves to reference the process. Sup- pose a user wants to terminate a process before it completes execution normally, and he knows the ID number is 782. He could issue a KILL(782) command that would cause the operating system to search through the queue of PCBs, find the PCB with ID 782, remove it from the queue, and deallocate it. Another example of information stored in the PCB is a record of the total amount of CPU time used so far by the suspended process. If the CPU becomes available and the operating system must decide which of several suspended processes gets the CPU, it can use the recorded time to make a fairFigure decision. 8.19 As a job progresses through the system toward completion, it passes through several states, as Figure 8.19 shows. The figure is in the form of a state transition diagram and is another example of a finite state machine. Each transition is labeled with the event that causes the change of state.
    [Show full text]
  • Low Contention Semaphores and Ready Lists
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Purdue E-Pubs Purdue University Purdue e-Pubs Department of Computer Science Technical Reports Department of Computer Science 1980 Low Contention Semaphores and Ready Lists Peter J. Denning T. Don Dennis Jeffrey Brumfield Report Number: 80-332 Denning, Peter J.; Dennis, T. Don; and Brumfield, Jeffrey, "Low Contention Semaphores and Ready Lists" (1980). Department of Computer Science Technical Reports. Paper 261. https://docs.lib.purdue.edu/cstech/261 This document has been made available through Purdue e-Pubs, a service of the Purdue University Libraries. Please contact [email protected] for additional information. LOW CONTENTION SEMAPHORES AND READY LISTS Peter J. Denning T. Don Dennis Jeffrey Brumfield Computer Sciences Department Purdue University W. Lafayette, IN 47907 CSD-TR-332 February 1980 Revised June 1980 Abstract. A method for reducing sema­ phore and ready list contention in mul­ tiprocessor operating systems is described. Its correctness is esta­ blished. Its performance is compared with conventional implementations. A method of implementing the ready list with a ring network is proposed and evaluated. This work was supported in part by NSF Grant MCS78­ 01729 at Purdue University. June 18, 1980 - 2 - THE PROBLEM Modern operating systems implement semaphores for synchron- izing multiple concurrent processes. Unless the primitive opera- tions for starting, stopping, and scheduling processes and for manipulating semaphores are well supported by the hardware, con- text switching and interprocess signaling can be major overheads [1]. To avoid these overheads, many operating systems use fast, but unreliable ad hoc methods for synchronizing processes.
    [Show full text]
  • Semaphores (Dijkstra 1965)
    Semaphores (Dijkstra 1965) n Semaphores have a non-negative integer value, and support two operations: n semaphore->P(): an atomic operation that waits for semaphore Semaphores & Monitors to become positive, then decrements it by 1 n semaphore->V(): an atomic operation that increments semaphore by 1, waking up a waiting P, if any. n Semaphores are like integers except: Arvind Krishnamurthy (1) non-negative values; Spring 2004 (2) only allow P&V --- can’t read/write value except to set it initially; (3) operations must be atomic: -- two P’s that occur together can’t decrement the value below zero. -- thread going to sleep in P won’t miss wakeup from V, even if they both happen at about the same time. Implementing semaphores Using interrupts P means “test” (proberen in Dutch) V means “increment” (verhogen in Dutch) class Semaphore { int value = 0; } n Binary semaphores: Semaphore::P() { n Like a lock; can only have value 0 or 1 (unlike the previous Disable interrupts; Semaphore::V() { “counting semaphore” which can be any non-negative integers) while (value == 0) { Disable interrupts; Enable interrupts; value++; Disable interrupts; Enable interrupts; } } n How to implement semaphores? Standard tricks: value = value - 1; Enable interrupts; n Can be built using interrupts disable/enable } n Or using test-and-set n Use a queue to prevent unnecessary busy-waiting n Question: Can we build semaphores using just locks? Using test&set How to use semaphores n Binary semaphores can be used for mutual exclusion: class Semaphore { int value = 0; initial value of 1; P() is called before the critical section; and V() is called after the int guard = 0; } critical section.
    [Show full text]
  • Synchronization
    Synchronization CS 4410 Operating Systems [R. Agarwal, L. Alvisi, A. Bracy, M. George, E. Sirer, R. Van Renesse] • Foundations • Semaphores • Monitors & Condition Variables 2 Semaphores • Definition • Binary Semaphores • Counting Semaphores • Classic Sync. Problems (w/Semaphores) - Producer-Consumer (w/ a bounded buffer) - Readers/Writers Problem • Classic Mistakes with Semaphores 3 What is a Semaphore? [Dijkstra 1962] Dijkstra introduced in the THE Operating System Stateful: • a value (incremented/decremented atomically) • a queue • a lock Interface: • Init(starting value) • P (procure): decrement, “consume” or “start using” • V (vacate): increment, “produce” or “stop using” No operation to read the value! Dutch 4410: P = Probeer (‘Try'), V = Verhoog ('Increment', 'Increase by one') 4 Semantics of P and V P(): P() { • wait until value >0 while(n <= 0) ; • when so, decrement n -= 1; value by 1 } V(): V() { • increment value by 1 n += 1; } These are the semantics, but how can we make this efficient? (doesn’t this look like a spinlock?!?) 5 Implementation of P and V P(): P() { • block (sit on Q) til n > 0 while(n <= 0) • when so, decrement value by 1 ; n -= 1; V(): } • increment value by 1 • resume a thread waiting on Q V() { (if any) n += 1; } Okay this looks efficient, but how is this safe? 6 Implementation of P and V P() { P(): acquire(&guard); • block (sit on Q) til n > 0 while(n <= 0) { waiting.enq(self); • when so, decrement value by 1 release(&guard); sleep(); acquire(&guard); V(): } • increment value by 1 n -= 1; release(&guard);
    [Show full text]
  • Parallel Programming Models III (Pdf)
    Shared Memory Programming Models III Stefan Lang Interdisciplinary Center for Scientific Computing (IWR) University of Heidelberg INF 368, Room 532 D-69120 Heidelberg phone: 06221/54-8264 email: [email protected] WS 15/16 Stefan Lang (IWR) Simulation on High-Performance Computers WS15/16 1/36 Shared Memory Programming Models III Communication by shared memory Semaphore rep. Reader-Writer problem PThreads Active Objects Stefan Lang (IWR) Simulation on High-Performance Computers WS15/16 2/36 Semaphore A semaphore is an abstraction of a synchronisation variable, that enables the elegant solution of multiple of synchronisation problems Up-to-now all programs have used active waiting. This is very inefficient under quasi-parallel processing of multiple processes on one processor (multitasking). The semaphore enables to switch processes into an idle state. We understand a semaphore as abstract data type: Data structure with operations, that fulfill particular properties: A semaphore S has a non-negative integer value value(S), that is assigned during creation of the Semaphore with the value init. For a semaphore S two operations P(S) and V(S) are defined with: P(S) decrements the value of S by one if value(S) > 0, otherwise the process blocks as long as another process executes a Voperation on S. V(S) frees another process from a Poperation if one is waiting (are several waiting one is selected), otherwise the value of S is incremented by one. Voperations never block! Stefan Lang (IWR) Simulation on High-Performance Computers WS15/16 3/36 Readers/Writers Problem ReadersLeser WritersSchreiber DatabaseDatenbank Two classes of processes, readers and writers, access a common database.
    [Show full text]