Examples of using Parallel computing in English and their translations into Korean
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Parallel computing.
Massively parallel computing.
Parallel Computing.
WebCL- Heterogeneous parallel computing in HTML5 web browsers.
Parallel computing has already entered the mass market and 3D games.
MapReduce is a programming model that simplifies parallel computing.
FPGA: Parallel computing technology with FPGA as core.
David A. Bader provides an IEEE listing of parallel computing sites.
We promised parallel computing benchmarks lately. Here we go….
AutoFormplus R3 offers more options in the parallel computing field.
Amdahl's law is often used in parallel computing to predict the theoretical speedup when using multiple processors.
David A. Bader provides an IEEE listing of parallel computing sites.
Unlike with parallel computing, grid computing projects typically have no time dependency associated with them.
PyOpenCL you access to the API for parallel computing with Python OpenCL.
He is widely published in the areas of algorithms and systems for highly distributed and parallel computing.
FCPC high performance embedded parallel computing platform is developed by BRAVO.
Published: August 28, 2009, by admin PyOpenCL provides access to APIs to OpenCL parallel computing with Python.
BRAVO spend 3 years on ARM cluster A/V parallel computing platform, provide low power, lowcost, high.
Logical value indicating whether to run Bayesian optimization in parallel, which requires Parallel Computing Toolboxâ„¢.
Depending on the application, parallel computing can speed things up by any where from 2 to 500 times faster(in some cases even faster).
Casting process simulation Forming The calculation methods and parallel computing technologies.
Leveraging the power of high performance parallel computing on the cloud, wind turbine structural analysis can now be performed in minutes rather than hours.
PyOpenCL provides access to APIs to OpenCL parallel computing with Python.
The AutoForm hydro solver now supports parallel computing achieving significant speed-up levels(comparable to AutoForm's incremental solver).
Use of a GPU is recommended and requires Parallel Computing Toolbox™.
And the CUDA, a parallel computing platform made by Nvidia, uses GPU hardware to perform accelerated interconversion of video file formats, which consequently releases your CPU.
The uniquely flexible and interoperable systems leverage interactivity, parallel computing, Spark, and Hadoop.
An incredibly cheap and surprisingly high performance parallel computing system that's not only valuable in education but can also solve some useful, real world problems.
Parallel computing may be seen as a particular tightly coupled form of distributed computing,[17] and distributed computing may be seen as a loosely coupled form of parallel computing.
For example, if 90% of the program can be parallelized, the theoretical maximum speed-up using parallel computing would be 10x no matter how many processors are used.