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which is exited once the enumerator is found to be empty Threads acquire a lock (using e n as the lock) and, inside of the critical region, accumulate up to c h u n k items from the enumerator by calling MoveNext and remem bering the C u r r e n t element in its private array Afterwards, e l ems C ount will be the number of elements taken, and it will invoke body on each element it took (if any) Notice that the loop termination condition occurs when the number of elements taken from the enumerator is fewer than the maximum that could have been taken; the only way this would arise is if a call to the enumerator 's MoveNext function returned f a l s e Note that this technique generalizes easily to other kinds o f loops that use predicates to determine when to exit a loop For example, by replacing the call to MoveNext with the invocation of a F u n c < boo l > and the call to C u r rent with an invocation of a F u n c < T>, we could parallelize a wh i l e loop There is one thing we must ensure, however: once the predicate evaluates to f a l se, it will always subsequently evaluate to fa l s e If this weren' t the case, the loop may not terminate appropriately when expected Scalability of this algorithm is going to be far less attractive than the index approaches shown earlier, unless the work done per element is huge The reason is that locking the enumerator is likely a significant scaling bottleneck As the size of c h u n k increases, the amount of time each thread spends inside the critical region also increases (because the loop complex ity depends directly on it) If Mov eNext is simple-as would be the case with any NET collection enumerators-then the cost per element can be expected to be fairly small; but if MoveNext is referencing a LINQ query that is streaming results from a database, for example, this code performs I/O. rdlc code 128 How to Generate Code 128 Barcode in RDLC Reports
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Have you tried anything so far? Have you tried searching this ijnn Google? Ok. If you still want some suggestions then check following article- inside of a critical region Also, larger chunk sizes mean that threads need to acquire the lock less frequently, which can aid in performance, but detracts from load balancing Yet another factor that impacts the frequency of lock acquisitions is the cost of the function body, which is invoked for each element As the number of threads increases, the contention at the lock also increases, meaning that for larger number of threads, bigger chunks may be better (assuming the cost of body outweighs that of MoveNext) In the end, there is no perfect answer other than to experiment for your particular scenarios If a data structure only offers an iterator based interface, it's often a bet ter idea to take one of two approaches One is to crack open its internals and devise your own data structure specific partitioning scheme For instance, a binary tree may not offer an indexer, but it's almost certainly a better idea to partition it by handing out independent subtrees in a divide and conquer style approach than to rely on the generic enumerator based partitioning Another alternative is to create your own data structure that allows for effi cient partitioning rdlc barcode 128 How to add Barcode to Local Reports (RDLC) before report ...
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