The open-source Python language is now supported by CUDA, Nvidia's parallel computing platform and programming model that "enables dramatic increases in computing performance by harnessing the power of GPUs."
At this year's GPU Technology Conference (GTC), Nvidia announced that the company's CUDA parallel programming technology has support for Python and consequently can take "full advantage of GPU acceleration for their high performance computing (HPC) and big data analytic applications."
This support comes from NumbaPro, a Python compiler in the new Anaconda Accelerate product from Continuum Analytics and is a result of the company's contribution of the CUDA compiler source code into the core and parallel thread execution backend of LLVM.
"Hundreds of thousands of Python programmers will now be able to leverage GPU accelerators to improve performance on their applications," said Travis Oliphant, co-founder and CEO of Continuum Analytics. "With NumbaPro, programmers have the best of both worlds: they can take advantage of the flexibility and high productivity of Python with the high performance of NVIDIA GPUs."
Anaconda Accelerate is available for Continuum Analytics' Anaconda Python offering and as part of the Wakari browser-based data exploration and code development environment.