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@ 2013/03/19The growing ranks of programmers using the Python open-source language can now take full advantage of GPU acceleration for their high performance computing (HPC) and big data analytics applications by using the NVIDIA CUDA parallel programming model, NVIDIA today announced.
Easy to learn and use, Python is among the top 10 programming languages with more than three million users. It enables users to write high-level software code that captures their algorithmic ideas without delving deep into programming details. Python's extensive libraries and advanced features make it ideal for a broad range of HPC science, engineering and big data analytics applications. Support for NVIDIA CUDA parallel programming comes from NumbaPro, a Python compiler in the new Anaconda Accelerate product from Continuum Analytics.
Easy to learn and use, Python is among the top 10 programming languages with more than three million users. It enables users to write high-level software code that captures their algorithmic ideas without delving deep into programming details. Python's extensive libraries and advanced features make it ideal for a broad range of HPC science, engineering and big data analytics applications. Support for NVIDIA CUDA parallel programming comes from NumbaPro, a Python compiler in the new Anaconda Accelerate product from Continuum Analytics.
