how to generate qr code in asp.net using c# Fine-grained concurrency in C#.NET

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Fine-grained concurrency
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Although code-based tasks are superficially similar to thread pool work items, the TPL is designed to let you use much smaller tasks than would work efficiently when using the thread pool directly. The TPL encourages fine-grained concurrency the idea is that you provide it with a large number of small work items, which gives it plenty of freedom to work out how to allocate that work across logical processors. This is sometimes described as overexpression of concurrency. The theory is that as newer computers come out with more and more logical processors, code that overexpresses its concurrency will be able to take advantage of the higher logical processor count.
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The TPL uses the CLR thread pool internally, so it might seem surprising that the TPL is able to handle small work items more efficiently, but the TPL provides access to some features added to the thread pool in .NET 4, which you can t use with the ThreadPool class. The ThreadPool class typically starts work in the order you queued it up, so it s a FIFO (first in, first out) queue. (This is absolutely not guaranteed by the documentation, but the fact that the ThreadPool has behaved this way for years means that changing this behavior would doubtless break lots of code.) But when you set up work as Task objects the thread pool works differently. Each logical processor gets its own separate queue, and typically processes tasks in its queue in LIFO (last in, first out) order. This turns out to be far more efficient in a lot of scenarios, particularly when the work items are small. This ordering is not strict, by the way; if one logical processor manages to empty its work queue while others still have plenty to do, the idle processor may steal work from another processors, and will do so from the back end of its queue. (If you re wondering about the rationale behind how the thread pool orders tasks, see the sidebar below.)
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LIFO Queues and Work Stealing
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Three of the thread pool s features per-logical-processor queues, LIFO ordering, and stealing from the end of the queue share a single goal: working efficiently with CPU caches. When possible, you want a task to be executed on the same logical processor that generated the work because that logical processor s cache probably already contains a lot of the information relating to the task. Handling the task on a different logical processor would mean shuffling data out of the originating logical processor and into the one running the task. That s why each logical processor has its own queue, and new tasks are allocated to the queue of the logical processor that creates them. The rationale behind LIFO ordering is that the most recently created tasks are the ones most likely to have associated data still in the cache, so the average throughput will be better if we handle those first. One reason work stealing between CPUs happens from the back end of the queue is that when stealing work from another logical processor you want to pick the item that is least likely to still have data sitting in the other logical processor s cache, to minimize the amount of data that may need to be moved. So in that case, the oldest item is the best bet. Another benefit of this is that it can reduce contention queues can be constructed in such a way that different CPUs can access opposite ends of the queue simultaneously.
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The examples we ve seen so far simply perform work and return no results. But a task can produce a result.
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