DV Hardware - bringing you the hottest news about processors, graphics cards, Intel, AMD, NVIDIA, hardware and technology!

   Home | News submit | News Archives | Reviews | Articles | Howto's | Advertise
 
DarkVision Hardware - Daily tech news
November 18, 2018 
Main Menu
Home
Info
News archives
Articles
Howto
Reviews
 

Who's Online
There are currently 169 people online.

 

Latest Reviews
Arctic BioniX F120 and F140 fans
Jaybird Freedom 2 wireless sport headphones
Ewin Racing Champion gaming chair
Zowie P-TF Rough mousepad
Zowie FK mouse
BitFenix Ronin case
Ozone Rage ST headset
Lamptron FC-10 SE fan controller
 

Follow us
RSS
 

NVIDIA CUDA adds Python support

Posted on Monday, March 18 2013 @ 16:52:07 CET by


NVIDIA logo
NVIDIA announced there's now Python support for CUDA:
The 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.

"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 at 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."

Expanded Access to Accelerated Computing Via LLVM
This new support for GPU-accelerated application development is the result of NVIDIA's contribution of the CUDA compiler source code into the core and parallel thread execution backend of LLVM, a widely used open source compiler infrastructure.

Continuum Analytics' Python development environment uses LLVM and the NVIDIA CUDA compiler software development kit to deliver GPU-accelerated application capabilities to Python programmers.

The modularity of LLVM makes it easy for language and library designers to add support for GPU acceleration to a wide range of general-purpose languages like Python, as well as to domain-specific programming languages. LLVM's efficient just-in-time compilation capability lets developers compile dynamic languages like Python on the fly for a variety of architectures.

"Our research group typically prototypes and iterates new ideas and algorithms in Python and then rewrites the algorithm in C or C++ once the algorithm is proven effective," said Vijay Pande, professor of Chemistry and of Structural Biology and Computer Science at Stanford University. "CUDA support in Python enables us to write performance code while maintaining the productivity offered by Python."

Anaconda Accelerate is available for Continuum Analytics' Anaconda Python offering, and as part of the Wakari browser-based data exploration and code development environment.




 



 

DV Hardware - Privacy statement
All logos and trademarks are property of their respective owner.
The comments are property of their posters, all the rest © 2002-2018 DM Media Group bvba