What Is a Mechanism for Threads to Synchronize?

Synchronization Machinery

Transactional programming

Maurice Herlihy , ... Michael Spear , in The Fine art of Multiprocessor Programming (2nd Edition), 2021

xx.1.4 Bug with compositionality

One drawback common to all the synchronization mechanisms nosotros have discussed so far is that they cannot hands exist equanimous. For case, suppose we want to dequeue an detail x from a queue

and enqueue it on some other queue

. The transfer must be atomic: Concurrent threads must not discover that x has vanished, nor that it is present in both queues. In

implementations based on monitors, each method acquires the lock internally, and then we cannot combine two method calls in this way.

There are, of form, ad hoc solutions: Nosotros could introduce a lock to exist acquired by any thread attempting an atomic modification to both

and

(in improver to the private locks for

and

). Such a lock requires knowing in accelerate the identities of the two queues, and it could be a bottleneck (no concurrent transfers). Alternatively, the queues could consign their synchronization state (say, via

() and

() methods), and rely on the caller to manage multiobject synchronization. Exposing synchronization state in this way would have a devastating effect on modularity, complicating interfaces and relying on callers to follow complicated conventions. As well, this approach does not work for nonblocking implementations.

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Resolved Signals

Peter J. Ashenden , ... Darrell A. Teegarden , in The Organisation Designer'southward Guide to VHDL-AMS, 2003

Example

Some asynchronous bus protocols use a distributed synchronization machinery based on a wired-and control signal. This is a single point driven by each module using active-low open-collector or open-drain drivers and pulled upwards by the coach terminator. If a number of modules on the bus need to wait until all are set up to go on with some operation, they use the control betoken as follows. Initially, all modules bulldoze the signal to the '0' country. When each is ready to proceed, it turns off its driver ('Z') and monitors the control signal. So long as any module is non nevertheless ready, the signal remains at '0'. When all modules are ready, the bus terminator pulls the signal up to the '1' land. All modules sense this modify and go on with the functioning.

Figure 15-nine shows an entity announcement for a bus module that has a port of the unresolved type std_ulogic for connection to such a synchronization control indicate. The compages body for a organization comprising several such modules is likewise outlined. The control signal is pulled upwards by a concurrent signal assignment argument, which acts as a source with a abiding driving value of 'H'. This is a value having a weak force, which is overridden by any other source that drives '0'. Information technology can pull the signal loftier only when all other sources drive 'Z'.

FIGURE 15-nine. An entity declaration for a bus module that uses a wired-and synchronization betoken, and an compages torso that instantiates the entity, connecting the synchronization port to a resolved point.

Figure 15-10 shows an outline of a behavioral compages body for the coach module. Each instance initially drives its synchronization port with '0'. This value is passed up through the port and used as the contribution to the resolved bespeak from the entity instance. When an case is set up to proceed with its operation, information technology changes its driving value to 'Z', modeling an open-collector or open up-drain commuter being turned off. The process then suspends until the value seen on the synchronization port changes to 'H'. If other instances are still driving '0', their contributions dominate, and the value of the signal stays '0'. When all other instances somewhen change their contributions to 'Z', the value 'H' contributed by the pull-up statement dominates, and the value of the signal changes to 'H'. This value is passed back down through the ports of each instance, and the processes all resume.

Figure 15-x. An outline of a behavioral architecture body for a motorbus module, showing utilize of the synchronization control port.

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Thread communication and synchronization on massively parallel GPUs

T. Ta , ... B. Jang , in Advances in GPU Research and Exercise, 2017

five Conclusion and Future Research Management

Throughout the affiliate, we discussed various thread communication and synchronization mechanisms bachelor in electric current GPUs. We presented several ways to accomplish fibroid-grained synchronization amid threads under different scopes, and the performance implications of each technique in particular situations. Nosotros discussed built-in atomic operations on regular, shared variables to avoid data race bug and too the bear on of such diminutive functions on performance for different GPUs. We presented the current trend toward more than fine-grained thread communication and synchronization that take been recently introduced every bit core functionalities in OpenCL 2.0 and HSA standards. Nosotros described the release-consistency-based memory model in OpenCL 2.0 by discussing concepts underlying that model and explaining how to correctly use newly introduced OpenCL two.0 functions to achieve fine-grained communication at the thread level.

There is interesting ongoing research on fine-grained thread communication and synchronization that is essential in order for current GPUs to handle irregular workloads efficiently at both the software and the architecture levels. Various lock-gratis concurrent data structures (doubly ended queue, linked list, skip list, etc.) that have been implemented using traditional coarse-grained synchronization and diminutive operations on GPUs [12, 13] can be more easily and efficiently implemented using fine-grained synchronization. The new HSA memory model opens more optimization opportunities for a class of irregular graph-based and mesh-based workloads whose functioning is limited by coarse-grained synchronization. At the compages level, implementation of such fine-grained thread communication mechanisms and the choice of a memory model for GPUs are interesting research directions [14–16]. Every bit GPUs become more tightly coupled with CPUs, supporting a single memory model for these different processors becomes an increasingly important and challenging research topic.

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Pitfalls and Bug of Manycore Programming

Ami Marowka , in Advances in Computers, 2010

2.iv A Uncomplicated Example—Cache Coherency and False Sharing

The post-obit example demonstrates the overhead costs of different basic synchronization mechanisms and the impact of enshroud coherency management and imitation-sharing situations on the performance. The example program scans an array of 100M integers and counts the odd numbers. The experiments were conducted on a laptop calculator equipped by Intel Core 2 Duo CPU T8100, 2.1 GHz, and 1 GB of RAM. For software, the compiler used was Intel C++ version eleven.0 on top of MS Windows XP Professional operating system. The compiler options were set to their default values. The parallelization was washed by OpenMP two.0. The results shown are an average time of x measurements.

Listings iii–9 nowadays different versions of the same program using different synchronization facilities and programming techniques. Figure 9 plots the running fourth dimension results. Listing 3 presents the series version of a counting plan that lasts 168 ms. Listing 4 presents the beginning OpenMP parallel version of the counting program that uses locks for protecting the shared counter count. In this case, the program runs 6286 ms which exhibit the very high overhead incurred by the parallelism using locks. The program version using critical-department for protecting the shared counter (Listing v) does not reach much better issue (6079 ms). Replacing the OpenMP critical directive with atomic directive (Listing vi) improves the performance dramatically (1206 ms). Now that the synchronization overhead is reduced to a minimum, the remaining overhead is mainly due to the cache coherency management.

Fig. 9. Overheads costs of different synchronization mechanisms and programming techniques.

Listing 3—Serial Counting of odd numbers.

#ascertain N 100000000

int a[Northward], count=0;

void serial ()

{

int i ;

for (i=0; i<N; i++)

if (a[i] % ii){

count++; // count odd numbers

}

}

}

The impact of the cache coherency management is reduced by using distributed counters (Listing 7). Each thread employs a private counter (counter [0] and counter [1]) and their values are summed at the cease of the counting. Now the full counting takes 120 ms, which is a speedup of one.4. The private counters are located adjacent to each other and thus liable to incur false-sharing situations. To eliminate these false-sharing situations, the counters are padded by dummy data that prevents them from sharing the same enshroud-line (Listing viii). The running time subsequently eliminating a fake-sharing situation is 104 ms, an improvement of 13.iii%, thus increasing the speedup to ane.61. The last experiment uses the OpenMP reduction performance (Listing 9). In this case, OpenMP implicitly creates private copies of the count variable for each thread. When the counting is over, the values of the individual counters are added into the global variable count. By using the OpenMP reduction operation, the running fourth dimension accomplished is 98 ms, a speedup of 1.71. Therefore, it is recommended to use ready-fabricated parallel constructs and parallel libraries, where possible, because they are optimized for the target machines.

List 4—Shared counter protected by locks.

#define N 100000000

int a[N], count=0;

int num_thrds = two;

void locks (int num_thrds)

{

int i ;

omp_lock_t lck ;

omp_init_lock(&lck) ;

#pragma omp parallel for num_threads (num_thrds)

for (i = 0; i<N; i++) /* i is individual by default */

if (a[i] % 2){

omp_set_lock(&lck) ;

count++;

omp_set_lock(&lck);

}

}

}

List 5—Shared counter protected past critical section.

#ascertain N 100000000

int a[Northward], count=0;

int num_thrds = 2;

void disquisitional (int num_thrds)

{

int i ;

#pragma omp parallel for num_threads(num_thrds)

for (i = 0; i<N; i++) /* i is private past default */

if (a[i] % 2){

#pragma omp critical

count++;

}

}

}

Listing half dozen—Shared counter protected past atomic operation.

#define Northward 100000000

int a[Northward], count=0;

int num_thrds = two;

void atomic (int num_thrds)

{

int i ;

#pragma omp parallel for num_threads(num_thrds)

for (i = 0; i<N; i++) /* i is private by default */

if (a[i] % ii){

#pragma omp diminutive

count++;

}

}

}

Listing seven—Distributed counters.

#define N 100000000

int a[N], count=0, counter [2] ;

int num_thrds = 2;

void distributed_counters(int num_thrds)

{

int i ;

#pragma omp parallel num_threads(num_thrds)

{

int id=omp_get_thread_num () ;

#pragma omp for

for (i = 0; i<N; i++) /* i is private by default */

if (a[i] % two) {counter[id]++;}

}

count = counter[0]+counter[ane] ;

}

Listing 8—Distributed counters with False-Sharing Emptying.

#define N 100000000

struct padding_int

{

int value ;

char dummy [threescore];

} counters [2];

int a[N], count=0;

int num_thrds = 2;

void distributed_counters_without_fs(int num_thrds)

{

int i ;

#pragma omp parallel num_threads(num_thrds)

{

int id=omp_get_thread_num () ;

#pragma omp for

for (i = 0; i<N; i++) /* i is private past default */

if (a [i] % 2) {counters [id]. value++;}

}

count = count [0]. value+count [ane]. value ;

}

Listing 9—Shared counter protected by reduction operation.

#define N 100000000

int a[N], count=0;

int num_thrds = 2;

void reduction (int num_thrds)

{

int i ;

#pragma omp parallel for reduction (+:count) num_threads(num_thrds)

for (i = 0; i<N; i++) /* i is private by default */

if (a[i] % 2) {count++;}

}

}

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Serendip Runtime

Malinda Kapuruge , ... Alan Colman , in Service Orchestration As Arrangement, 2014

v.4 Data synthesis of tasks

In Section four.6, we have described how the data synthesis and synchronisation mechanism is designed to form a membrane (the interaction membrane) effectually the composite. The membrane is the border in which transformations betwixt internal letters (due to role–role interactions) and external messages (function-histrion interactions) take place. An external interaction is composed possibly from internal interactions when a service invocation needs to be formulated. Conversely, an external interaction tin cause further internal interactions. Transformations need to be carried to propagate information across the membrane. The membrane isolates the external interactions from the (internal) core processes (and vice versa) to provide organisational stability. In order to support this concept, the design of the Serendip runtime needs to address a number of challenges.

i.

The request to complete a chore needs to be composed from the information derived from a single or possibly multiple internal letters. In the case of multiple messages being used, they tin make it in any gild. The runtime should accommodate such unpredictability in internal message ordering.

two.

Multiple processes can run simultaneously. Multiple internal messages of the same blazon (eastward.g. CO_TT.mOrderTow.Req) merely belonging to different process instances (e.g. p001, p002) can arrive at the part simultaneously. The bulletin synthesis mechanism of the runtime should be able to deal with such parallelism.

3.

Sending a request to the player needs to be synchronised according to the task dependencies divers in the behaviour units (e.1000. bTowing) of the organisation. The message synthesis mechanism should provide support for such synchronisation.

iv.

The response from the player may be used to create a single or multiple internal interactions. The responses (to multiple requests) may arrive in any club irrespective of the order in which the requests are made. For case, if towing requests are made to the FastTow service in the order of procedure instances p001→p002, the responses may come in the lodge of p002→p001. The runtime should be able to handle the unpredictability in external message ordering.

5.4.1 The role design

In order to address these challenges, the runtime is designed as shown in Effigy 5.6, which gives a zoomed-in view of an instantiated function composition at runtime. Every bit shown, a part instance contains four bulletin containers to store the messages and a bulletin analyser. The purpose of the message analyser is twofold, i.e. data synthesis and synchronisation.

Figure v.half-dozen. Information synthesis and synchronisation design.

1.

Synthesis performs the data transformations across (in and out of) the membrane. The message analyser performs two types of data transformations. These two transformations are named according to the perspective of the composite.

a.

Out-Transformations (Out-T) transform internal letters to external letters. We call the used internal messages the source messages and the generated external message the out-bulletin.

b.

In-Transformations (In-T) transform external messages to internal messages. We call the used external message the in-message and we call the generated internal messages the result messages.

ii.

Synchronisation: Synchronises the out-transformation in the behaviour layer by specifying the ordering of task executions and the reception of source letters. Note that the in-transformation is not synchronised with the behaviour layer, because, as before long as a message is received from the player, the bulletin is in-transformed to create the internal result messages. Nevertheless, runtime makes sure that the estimation of consequence letters via the contracts (Section 5.iii.2) trigger events conforming to the mail-result pattern of a given task.

In order to support the two transformations and the synchronisation, there are iv message containers in a part that the message analyser will use to pick and drib letters.

•

PendingOutBuffer: The internal messages (source letters) flowing from the adjoining contracts are initially buffered in here.

•

OutQueue: Once out-transformed, the external letters from role to the player (out-messages) are placed in here.

•

PendingInQueue: The external messages received from the histrion (in-letters) are initially placed here.

•

RouterBuffer: In one case in-transformed, the internal messages (result letters) fix to be routed to other roles (across contracts) are placed here.

5.four.2 The transformation process

The consummate bulletin transformation process is detailed here.

Synchronisation footstep:

1.

When the behaviour layer has identified that task T _i of process instance PI _j is set up for execution, the message analyser of the obligated role is notified.

Out-Transformation steps:

2.

The bulletin analyser picks the relevant source messages with the same process identifier PI _j from the PendingOutBuffer equally specified in the task description T _i .

three.

The message analyser performs the out-transformation to generate the out-bulletin. This may include enriching the information of the message and transforming the message to the expected format. Then, the out-message is marked with the same procedure identifier PI _j and placed in the OutQueue.

4.

The underlying message commitment mechanism (e.yard. ROAD4WS for Spider web services [260]) delivers the message from the OutQueue to the player. So, the role player executes job T _i of PI _j .

In-Transformation steps:

5.

The underlying message delivery machinery receives the response (i.east. the in-message) from the player and places it in the PendingInQueue. The message commitment mechanism ensures that the in-message is marked with the same process identifier PI _j , e.g. via a synchronous Web service request.

6.

The message analyser picks the messages from PendingInQueue and performs the in-transformation equally specified in task T _i to create issue letters.

7.

The created outcome messages are marked with the same process identifier PI _j and placed in the RouterBuffer to be routed across the bordering contracts (towards suitable roles). So, these contracts trigger events by interpreting these messages equally explained in Department five.three.ii. The runtime (via Event Observer, Department 7.1.ii) makes sure that the triggered events conform to the post-event pattern of the corresponding task.

Let u.s.a. consider a specific instance scenario to clarify these steps using the task tTow of part TT. Offset, the behaviour layer determines that the chore tTow of process instance p001 has become do-able (step 1). The source messages of the task tTow (CO_TT.mOrderTow.Req, GR_TT.mSendGRLocation.Req) that belong to the aforementioned procedure instance (i.e. with p001) are then picked from PendingOutBuffer (step ii). Then, these source letters are transformed (pace 3) to create the out-message (TT.tTow.Req), which is the bulletin delivered to the player (step 4). When the chore is complete (i.eastward. auto has been towed) and the thespian responds, the response message or the in-bulletin (TT.tTow.Res) is placed in the PendingInQueue (step v). The underlying message delivery mechanism makes sure that the aforementioned pid of the request is associated with the response. Then TT.tTow.Res is picked and transformed to create two result messages, i.e. CO_TT.mOrderTow.Res and GR_TT.mSendGRLocation.Res (step 6). These issue messages are again associated with the same pid of the in-bulletin. So, these issue messages are placed in the RouterBuffer (pace vii) to exist routed across the relevant roles, i.east. CO and GR via adjoining contracts, i.e. CO-TT and GR_TT.

This role and transformation pattern has been able to address the same challenges.

Challenge one: The PendingOutBuffer provides the storage for messages to be buffered. The messages are picked based on the synchronisation request rather than the guild in which they arrive. This addresses the challenge of unpredictability in-message ordering.

Challenge two: All the messages are annotated with the procedure case identifier. Therefore, the same type of messages of different process instances can be uniquely identified. This addresses the challenge posed by the parallelism in process execution.

Challenge 3: The bulletin analyser is synchronised with the behaviour layer of the arrangement. The out-transformation is carried out merely when the task becomes practise-able. As such, the bulletin synthesis machinery enables the synchronisation required.

Claiming 4: The message transformations are carried out in an asynchronous fashion within the composite. The bulletin containers allow a separation betwixt the role and the bulletin delivery mechanism that serves the Out/InQueues outside the membrane. The function does not need to wait for the response from the player. The message analyser operates in an asynchronous manner whereas the bulletin commitment (player service invocation) may operate in a synchronous or an asynchronous style (Section 7.2.5). Multiple threads in the message delivery machinery may spawn to serve the messages in the OutQueue too as to insert messages in the InQueue when the thespian responds (the actor implementation demand to back up multi-threaded serving). In this way, the responses from the player may arrive in any order unlike from the request guild.

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Concurrency

Michael Fifty. Scott , in Programming Linguistic communication Pragmatics (3rd Edition), 2009

Scheduler-Based Synchronization

The problem with decorated-expect synchronization is that it consumes processor cycles, cycles that are therefore unavailable for other ciphering. Busy-wait synchronization makes sense only if (1) i has zip better to do with the current processor, or (two) the expected await fourth dimension is less than the time that would be required to switch contexts to some other thread and so switch back again. To ensure acceptable performance on a wide variety of systems, most concurrent programming languages employ scheduler-based synchronization mechanisms, which switch to a different thread when the one that was running blocks.

In the following subsection nosotros consider semaphores, the nearly common course of scheduler-based synchronization. In Section 12.4 we consider the higher-level notions of monitors provisional critical regions, and transactional memory. In each example, scheduler-based synchronization mechanisms remove the waiting thread from the scheduler's ready list, returning it only when the awaited condition is true (or is probable to be true). By contrast, a spin-then-yield lock is still a busy-wait machinery: the currently running process relinquishes the processor, but remains on the ready listing. Information technology will perform a test_and_set operation every time every time the lock appears to exist free, until it finally succeeds. It is worth noting that busy-wait synchronization is more often than not "level-independent"—information technology can be idea of as synchronizing threads, processes, or processors, every bit desired. Scheduler-based synchronization is "level-dependent"—it is specific to threads when implemented in the linguistic communication run-time organization, or to processes when implemented in the operating arrangement.

Example 12.35

The Bounded Buffer Problem

We will use a bounded buffer abstraction to illustrate the semantics of various scheduler-based synchronization mechanisms. A bounded buffer is a concurrent queue of express size into which producer threads insert data, and from which consumer threads remove information. The buffer serves to fifty-fifty out fluctuations in the relative rates of progress of the two classes of threads, increasing system throughput. A correct implementation of a bounded buffer requires both atomicity atomicity and condition synchronization: the former to ensure that no thread sees the buffer in an inconsistent state in the middle of some other thread'south operation; the latter to force consumers to wait when the buffer is empty and producers to wait when the buffer is full.

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Hardware-Software Prototyping from LOTOS

LUIS SÁNCHEZ FERNÁNDEZ , ... WOLFGANG ROSENSTIEL , in Readings in Hardware/Software Co-Pattern, 2002

6.i.2 HARPO

LOTOS communications imply synchronising, exchanging of data and like-minded on the information among the parties. This scheme can be translated to VHDL by means of a protocol that has been implemented in the HARPO tool. The protocol is implemented in a library of components.

A LOTOS process is translated to a VHDL entity which contains one primary procedure and several instantiations (one for each gate) of the library components. The mentioned components are controlled past the chief processes and perform the synchronisations when required. Another do good is the possibility for parallellising several synchronisations, as different instantiations of these components can be triggered in parallel. The components are two: Synch_Val for sending and Synch_Var for receiving (see Figure 8). Nosotros apply three signals in VHDL for each LOTOS gate. gate_r and gate_a are used to perforn the handshaking protocol and gate is used to bear the data value send from the emitter to the receiver.

Figure 8. Implementation of a gate interface in HARPO.

The protocol that links the library components Synch_Val and Synch_Var is one of the possible implementations of the LOTOS synchronisation mechanism between two processes willing to perform an upshot on a mutual gate. Let us report a simple synchronisation betwixt 2 LOTOS processes, i offering a variable and the other offer a value. For the interaction to take identify, iii requirements are necessary:

one.

The two processes must be ready to interact, i.e., they wait for each other.

2.

The value must exist of the aforementioned sort of the variable.

3.

Both of them will continue their behaviour after the synchronisation simultaneously.

The 2d condition is warranted in this approach by imposing on LOTOS gates a given direction and type.

Let u.s. describe the protocol used past HARPO. There are four stages in order:

one.

Synch_Val sets gate_r to 01 and waits for a 01 at gate_a.

2.

Synch_Var waits for a 01 at gate_r and then information technology sets gate_a to 01. This stride indicates that both processes are willing to synchronise on this gate.

3.

Information is exchanged. When valid data is already at gate. Synch_Val sets gate_r to 00 and waits for a 10 or a 11 in gate_a. Synch_Var waits for a 00 in gate_r and it sets gate_a to 10 if the data is accepted, or to eleven otherwise.

4.

Processes continue their execution. If Synch_Val received a ten information technology sets gate_r to 10. meaning that the synchronisation has finished successfully: if the value received was xi, indicating that some of the receivers did not accept the value, it sets gate_r to 11, which implies that the synchronisation has not occurred and the information is not valid.

Synch_Val can set gate_r to 11 fifty-fifty if it had received a 10, and is basically due to the being of several possible synchronisations to commit, and the necessity of discarding all only one. It is important to annotation that following this protocol the writer is the one who decides finally if a synchronisation takes place or not one time the reader has accepted information technology. We volition take advantage of this when we build the interface.

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Causal Consistency

Matthieu Perrin , in Distributed Systems, 2017

iv.5 Specific behaviors

The full lodge that describes the linearization of sequential consistency is a causal order: information technology contains the process order and any outcome has a cofinite causal futurity considering its (finite) position in the linearization determines its causal past. Additionally, equally the order is total, the concurrent present of all the events is empty. The opposite is too truthful: a weakly causally consistent history in which each consequence has an empty concurrent present is sequentially consistent.

This means that it is not necessary to manage synchronizations in the same program several times over. More precisely, the histories generated by a distributed application using a shared object in its implementation are restricted both by the specification of the shared object (its sequential specification and its consistency benchmark) and past the application itself (for instance, if an operation of the object is never called in the implementation of the application, this operation volition not be present in the generated histories). If a program mechanism guarantees that two dissimilar operations are always causally dependent, a weakly causally consistent object behaves similar its sequentially consistent counterpart. Let us imagine, for example, a game where each player plays past turn, such every bit chess. Co-ordinate to the rules of the game (the programme), each role player (a process) must expect for the other player to complete their plough (causal dependency between the displacement of two pieces, or 2 updates) in lodge to move their slice across the board (the shared object). Using weak causal consistency rather than sequential consistency to implement the board will in no way change the program behavior.

In fact, in the to a higher place instance, the causal order is not total unless the chess clock rings between each plow (external synchronization mechanism). If non, the role player who is not currently moving a piece (update) must look at the board (query) to know when they can play. The original commodity on causal memory [AHA 95] justifies the interest in this past the fact that any history in which two writes are always causally ordered is sequentially consequent. Suggestion 4.6 proves that this is, in fact, a property of weak causal consistency: any weakly causally consistent history in which all the writes are ordered two by two is sequentially consistent (SC).

Proposition four.6

Permit an ADT T and a concurrent history H ∈ WCC(T). If, for any pair of updates (u, u′) ∈ U_T,H ², u ⤏ u′ or u′ ⤏ u, then H ∈ SC(T).

Proof.– Let $T\in \mathcal{T}$ and H ∈ WCC(T) such that for any pair of updates (u, u′) ∈ U_T,H ², u ⤏ u′ or u′ ⤏ u.

Let   ≤   be a total lodge on E_H , which extends ⤏, and permit l be the unique linearization of lin(H ^≤). Every bit   ↦   ⊂ ⤏   ⊂ ≤, fifty ∈ lin (H). Allow usa assume that l ∉ Fifty(T). As the transition system for T is deterministic, there exists a not-empty, finite prefix for l which does not belong to L(T). Let l′ ∈ Σ^⋆ and e ∈ East_H such that l′   ·   Λ(e) is the shortest such prefix. As H ∈ WCC(T), there exists a linearization in lin(H ^⤏[⌊east⌋_⤏/{due east}]) ∩ L(T) of the course l′′   ·   Λ(e) because e is the maximum for ⌊e⌋_⤏ according to ⤏. Notwithstanding, every bit l′ and l″ have the aforementioned updates ordered in the same club, because ⤏   is total for the updates, l′ and l″ atomic number 82 to the same state. In these conditions, it is absurd to have l″   ·   Λ(eastward) ∈ L(T), fifty′∈ L(T) and fifty′   ·   Λ(e) ∉ L(T). Thus, 50 ∈ L(T) and H ∈ SC(T).

A unproblematic way to utilise this property (though ane that has depression tolerance for crashes) is to use a synchronization chip. A programme implemented according to this strategy uses, in improver to a shared object representing the data, a bit whose value continuously indicates the identifier for a process. Only the process indicated by the bit is allowed to update the commencement object. When a procedure finishes its updates, it indicates another process by writing its identifier onto the chip. Such a strategy guarantees that ii updates are always causally ordered. Proposition 4.6 thus allows for an affirmation that in this state of affairs weak causal consistency, applied in the composition of the first object and the chip, offers exactly the same quality of service every bit sequential consistency, only at a much lower cost.

The suggestion can too exist applied to the other causal criteria discussed in this chapter, which are stronger than weak causal consistency. Additionally, proposition iv.seven proves that causally convergent histories, in which no update is incomparable with a query according to the causal gild, are besides sequentially consequent. Causal convergence reinforces update consistency,in which some queries may seem incorrect. This proffer affirms that the simply queries that may appear wrong in causal convergence are those which are unequalled with at to the lowest degree one update based on causal order.

Proposition four.seven

Let there be an ADT T and a concurrent history H ∈ CCv(T) such that for any u ∈ U_T,H and q ∈ Q_T,H, u ⤏ q or q ⤏ u. Thus, H ∈ SC(T).

Proof.– Permit $T\in \mathcal{T}$ and H ∈ CCv(T) such that for whatsoever u ∈ U_T,H and q ∈ Q_T,H , u ⤏ q or q ⤏ u. Equally H ∈ CCv(T), there exists a total order, ≤ that contains ⤏   and, for any e ∈ E_H , a linearization l_{due east}   ·   Λ(east) ∈ lin (H ^≤[⌊east⌋_⤏/{east}] ∩ L(T).

Let l be the unique linearization for lin(H ^≤). As   ↦   ⊂ ≤, l ∈ lin(H). Let us assume that l ∉ L(T). As in the proffer 4.6, l has a prefix, l′   ·   Λ(due east) ∉ 50(T) where l′ ∈ L(T). The consequence eastward cannot be labeled a pure update every bit, when the transition system for T is consummate, any pure update may take place in any state, and therefore, particularly in the state obtained later the execution of l′. The event east cannot, therefore, exist a query. Thus, by the hypothesis, it is causally ordered with all the updates of that history. As the full social club, ≤, respects the causal order, ⤏, the updates in the past of east, according to causal order and according to the total social club, are exactly the aforementioned: ⌊eastward⌋_⤏ ∩ U_T,H   =   ⌊e⌋_≤ ∩ U_T,H . Nosotros tin deduce from this that l_e and l′ accept the same updates in the same order and that it is thus impossible that l_eastward   ·   Λ(due east) ∈ L(T), l′ ∈ Fifty(T) and l′   ·   Λ(e) ∉ L(T). Finally, fifty ∈ L(T) and H ∈ SC(T).

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A Survey of Switched Ethernet Solutions for Real-fourth dimension Audio/Video Communications

Xiaoting Li , Laurent George , in Building Wireless Sensor Networks, 2017

i.2.ii.three IEEE 1722

IEEE 1722 is a Layer 2 AVB transport protocol, also chosen AVTP. It enables interoperable streaming through bridges by defining media formats and encapsulations, media synchronization mechanisms likewise equally stream Multicast Address Allocation Protocol (MAAP). Information technology requires that all devices sending, receiving or forwarding stream data support services provided by IEEE 802.1AS for synchronization as well as IEEE 802.1Qat SRP and 802.1Qav for Quality of Service (QoS).

IEEE 1722 supports raw and compressed audio/video data formats of applications using IEC 61883. Each stream has a unique ID and can exist streamed from a Talker to one or several Listeners based on a multicast address allocated by the MAAP. Listeners can be rendering devices like multi-display (compound) screens.

Each stream data is encapsulated in a standard Ethernet Layer 2 frame with an inserted presentation time. The presentation time is the fourth dimension at which this audio/video stream data should be rendered on the destination devices. It is the Talker who is responsible for setting the presentation time by adding the worstcase transmission delay of the data to the sampled fourth dimension according to the IEEE 802.1AS clock. Based on a synchronized presentation time, all the rendering devices play the stream at the same time.

IEEE 1722 also supports time-sensitive command stream from field buses, e.g. Tin, FlexRay and LIN, which are connected to AVB Ethernet through a gateway.

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Offload

Jim Jeffers , James Reinders , in Intel Xeon Phi Coprocessor Loftier Performance Programming, 2013

Restrictions on offloaded code using shared virtual memory

Offloaded code using virtual shared memory has the following restrictions:

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Multiple host processor threads can execute meantime while i host processor thread offloads a section of lawmaking. In this example, synchronization mechanisms such as locks, atomics, mutexes, OpenMP atomic operations, OpenMP critical, OpenMP taskwait, OpenMP and barriers exercise not piece of work between the host processor code and code that is offloaded to the coprocessor. Nevertheless, if parallelism on the host processor is enabled using OpenMP, then OpenMP synchronization at the terminate of a parallel region is guaranteed to work fifty-fifty if some part of the OpenMP parallel region has been offloaded to the coprocessor.

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Exception handling may exist done as usual within lawmaking running on the processor and within code running on the coprocessor. Then exceptions can be raised, caught, and handled on the processor, or raised, caught, and handled on the coprocessor. However it is not possible to propagate an exception from the coprocessor to the processor.

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Virtual shared memory classes that allocate and gratuitous memory must use either using the _Offload_shared_malloc() and _Offload_shared_free() or _Offload_shared_aligned_malloc() and _Offload_shared_aligned_free() APIs instead of standard allocate and gratis APIs. For an example, run into installdir/Samples/en_US/C++/mic_samples/LEO_tutorial/tbo_sort.c(/opt/intel/composer_xe_2013 is the default installdir directory at the fourth dimension we are writing this). Standard Template libraries which provide classes that allocate and free their own retention are not usable currently with _Cilk_shared unless they are modified to use the _Offload_shared_* specific APIs mentioned above.

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Runtime Type Data (RTTI) is not supported under the Shared Virtual memory programming method. Specifically, use of dynamic_cast<> and typeid() is non supported.

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Source: https://www.sciencedirect.com/topics/computer-science/synchronization-mechanism

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