• Welcome to TechPowerUp Forums, Guest! Please check out our forum guidelines for info related to our community.

NVIDIA CUDA Gets Python Support

btarunr

Editor & Senior Moderator
Staff member
Joined
Oct 9, 2007
Messages
34,912 (9.08/day)
Likes
17,723
Location
Hyderabad, India
System Name Crypto-plague Survival Kit
Processor Intel Core i7-4770K
Motherboard ASUS Z97-A
Cooling Xigmatek Aegir CPU Cooler
Memory 2x 8GB Kingston HyperX Beast DDR3-1866
Video Card(s) 2x ZOTAC GeForce GTX 970
Storage ADATA SU800 512GB + Intel SSD320 120GB + Patriot WildFire 120GB
Display(s) Samsung U28D590 28-inch 4K UHD
Case Cooler Master CM690 1st Gen
Audio Device(s) Creative Sound Blaster Recon3D PCIe
Power Supply Corsair HX850W
Mouse Razer Abyssus
Keyboard Microsoft Sidewinder X4
Software Windows 10 Pro
#1
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.
 
Joined
Nov 13, 2009
Messages
5,614 (1.82/day)
Likes
1,678
Location
San Diego, CA
System Name White Boy
Processor Core i7 3770k @4.6 Ghz
Motherboard ASUS P8Z77-I Deluxe
Cooling CORSAIR H100
Memory CORSAIR Vengeance 16GB @ 2177
Video Card(s) EVGA GTX 680 CLASSIEFIED @ 1250 Core
Storage 2 Samsung 830 256 GB (Raid 0) 1 Hitachi 4 TB
Display(s) 1 Dell 30U11 30"
Case BIT FENIX Prodigy
Audio Device(s) none
Power Supply SeaSonic X750 Gold 750W Modular
Software Windows Pro 7 64 bit || Ubuntu 64 Bit
Benchmark Scores 2017 Unigine Heaven :: P37239 3D Mark Vantage
#3
good news IMO
 
Joined
Feb 8, 2012
Messages
2,835 (1.25/day)
Likes
2,049
Location
Zagreb, Croatia
System Name Windows 7 64-bit Core i5 3570K
Processor Intel Core i5 3570K @ 4.2 GHz, 1.26 V
Motherboard Gigabyte GA-Z77MX-D3H
Cooling Scythe Katana 4
Memory 4 x 4 GB G-Skill Sniper DDR3 @ 1600 MHz
Video Card(s) Gainward NVIDIA GeForce GTX 970 Phantom
Storage Western Digital Caviar Blue 1 TB, Seagate Baracuda 1 TB
Display(s) Dell P2414H
Case CoolerMaster Silencio 550
Audio Device(s) VIA HD Audio
Power Supply Corsair TX v2 650W
Mouse Steelseries Sensei
Keyboard CM Storm Quickfire Pro, Cherry MX Reds
Software MS Windows 7 Enterprise 64-bit SP1
#4
How much does this differ from PyCuda?
I believe PyCuda is for classic python interpreter, and this is about NumbaPro, a Python compiler in the new Anaconda Accelerate product from Continuum Analytics.