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GPU621/NoName

371 bytes added, 19:17, 3 December 2016
Asynchronous Multi-Threading
===Creating and executing Threads===
====OpenMp====
Inside a declared OpenMp parallel region, if not specified via an environment variable OMP_NUM_THREADS or the library routine omp_get_thread_num() , OpenMp will automatically decide how many threads are needed to execute parallel code.
An issue with this approach is that OpenMp is unaware how many threads a CPU can support. A result of this can be OpenMp creating 4 threads for a single core processor which may result in a degradation of performance.
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====C++ 11====
C++ 11 Threads on the contrary always required to specify the number of threads required for a parallel region. If not specified by user input or hard-coding, the number of threads supported by a CPU can also be accurately via the std::thread::hardware_concurrency(); function.
OpenMp automatically decides what order threads will execute. C++ 11 Threads require the developer to specify in what order threads will execute. This is typically done within a for loop block. Threads are created by initializing the std::thread class and specifying a function or any other callable object within the constructor.
A future is an object that can retrieve a value from some provider object (also known as a promise) or function. Simply put in the case of multithreading, a future object will wait until its associated thread has completed and then store its return value.
To retrieve or construct a future object, these functions may be used.
* Async * promise::get_future * packaged_task::get_future
However, a future object can only be used if it is in a valid state. Default future objects constructed from the std::async template function are not valid and must be assigned a valid state during execution.
A std::future references a shared state that cannot be shared to other asynchronous return objects. If multiple threads need to wait for the same shared state, std::shared_future class template should be used.
===Conclusion===
 
In conclusion while OpenMp is and still continues to be a viable option in multi-threading, it lacks the some of outlined features and lacks low-level control. While C++ 11 standard libarary multi-threading can be more difficult to learn, is supported by virtually all C++ 11 compilers and offers a low-level interaction between hardware threads.

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