PATTERNO LIBRARY HOW TO
PATTERNO LIBRARY SERIAL
PATTERNO LIBRARY PATCH
PATTERNO LIBRARY CODE

PATTERNO LIBRARY PATCH

The patterns labeled RGB start with a specific color patch in the upper left corner.

The columns (top to bottom) show the color from 100% luminance to 0% luminance (black).

The patterns labeled HSV show the color in rows (left to right) from 100% saturation to no color (greyscale).

The columns (top to bottom) show the color from 100% luminance (white) to 0% luminance (black).

The patterns labeled HSL show the color in rows (left to right) from 100% saturation (full color) to no color (greyscale).

The numbers at the bottom of each patch is that patchвЂ™s RGB (or triplet) value. These values can be identified on each patch by the identifying numbers.

Each patch in each test pattern has a specific value for the Hue, Saturation, and Value (luminance) for each color.

PATTERNO LIBRARY HOW TO

Related Topics TitleДescribes the role of tasks and task groups in the PPL.Дescribes how to use parallel algorithms such as parallel_for and parallel_for_each.Дescribes the various parallel containers and objects that are provided by the PPL.Д®xplains how to cancel the work that is being performed by a parallel algorithm.Дescribes the Concurrency Runtime, which simplifies parallel programming, and contains links to related topics.вЂ‹The following test patterns are used for color checker tests.

PATTERNO LIBRARY SERIAL

Therefore, you should not expect linear performance improvements between the serial and parallel versions of this example. The performance of parallel_for_each is bounded by the operation that finishes last. serial time: 9250 msД®ach iteration of the loop requires a different amount of time to finish. The following sample output is for a computer that has four processors.

Results1.push_back(make_tuple(n, fibonacci(n))) Use the for_each algorithm to compute the results serially. The results of the parallel computation. The results of the serial computation. Calls the provided work function and returns the number of milliseconds Note that the example uses a naГЇve method to compute the Fibonacci numbers however, this method illustrates how the Concurrency Runtime can improve the performance of long computations. The concurrent_vector class enables each loop iteration to concurrently add elements without the requirement to synchronize write access to the container.Д«ecause parallel_for_each acts concurrently, the parallel version of this example must sort the concurrent_vector object to produce the same results as the serial version. The parallel version performs the same task, but uses the PPL concurrency::parallel_for_each algorithm and stores the results in a concurrency::concurrent_vector object. The serial version uses the C++ Standard Library std::for_each algorithm to traverse the array and stores the results in a std::vector object. The example also prints to the console the time that is required to perform both computations. Both computations act on a std::array object. It computes several Fibonacci numbers serially and in parallel.

The following example demonstrates many features of the PPL. The PPL provides a programming model that resembles the C++ Standard Library. Parallel containers and objects: generic container types that provide safe concurrent access to their elements Parallel algorithms: generic algorithms that works on top of the Concurrency Runtime to act on collections of data in parallel Task Parallelism: a mechanism that works on top of the Windows ThreadPool to execute several work items (tasks) in parallel The PPL also lets you develop applications that scale by providing alternatives to shared state.

PATTERNO LIBRARY CODE

It raises the level of abstraction between your application code and the underlying threading mechanism by providing generic, type-safe algorithms and containers that act on data in parallel. The PPL builds on the scheduling and resource management components of the Concurrency Runtime. The Parallel Patterns Library (PPL) provides an imperative programming model that promotes scalability and ease-of-use for developing concurrent applications.

Patterno library