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
January 23, 2018 
Main Menu
News archives

Who's Online
There are currently 511 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

NVIDIA working with partners to deliver GPU Computing software

Posted on Tuesday, November 17 2009 @ 16:04:34 CET by

NVIDIA announced its cooperating with its ecosystem partners to deliver, over the next few months, a broad set of software release to developers using GPU Computing in their work. Here's a snip from the press release:
These updates feature major releases across a broad spectrum of GPU Computing development languages, tools and libraries. Included are updates from NVIDIA for its CUDA(TM) C compiler, with additional support for C++ and its upcoming GPU codenamed "Fermi." NVIDIA is also releasing its R195 driver that includes new extensions to its OpenCL 1.0 conformant driver and toolkit, and a beta release of the NVIDIA(R) code name Nexus, the industry's first development environment for massively parallel computing, which is integrated into Microsoft Visual Studio.

Alongside NVIDIA's own updates, several partner releases from industry leaders in software tools are available now, including The Portland Group's CUDA Fortran solution, Allinea's Distributed Debugging Tool (DDT) and the TotalView debugger.

"The only effective way to scale performance in demanding applications is to move to a parallel computing model," said Sanford Russell, general manager, GPU Computing software at NVIDIA. "The NVIDIA CUDA architecture facilitates this critical transition with its broad industry support and network of software consultants and training resources for massively parallel computing."

Updates to NVIDIA and its partners' parallel computing development tools include the following:

CUDA Toolkit 3.0 Beta: With the CUDA Toolkit 3.0 Beta, developers can start developing applications today for the NVIDIA Fermi architecture. This beta release includes features such as ECC reporting, Dual DMA Engine, Concurrent Kernel Execution and NVIDIA Fermi HW debugging support in cuda-gdb. Performance profiling is included for both CUDA Visual Profiler and the OpenCL Visual Profiler. Also included is support for a new unified interoperability API for Direct3D and OpenGL including Direct3D 11.

OpenCL 1.0 Extensions: NVIDIA is the only vendor supporting OpenCL features beyond the minimum conformance level. New extensions released by NVIDIA include support for double precision, OpenGL interoperability and the new OpenCL Installable Client Device (ICD). These new features supplement existing NVIDIA-only support for 2D image, 32-bit atomics and byte addressable stores.

NVIDIA "Nexus," the codename for the industry's first development environment for massively parallel GPU applications, integrated into Microsoft Visual Studio IDE: Comprised of a Debugger, Performance Analyzer and Graphics Inspector, this beta release gives GPU Computing developers an immediate boost in productivity through common and easy to use tools.

The Portland Group (PGI) -- CUDA Fortran: Production release of the world's first Fortran compiler compatible with the NVIDIA CUDA-enabled GPUs. CUDA Fortran will accelerate the adoption of GPU Computing in areas where applications are written in Fortran, such as ocean modeling, weather forecasting, environmental modeling, seismic analysis, bioinformatics and other areas.

Professional HPC Debugging Solutions from Allinea and

TotalView were also launched this week. These tools provide CUDA GPU features that complement existing capabilities for parallel debugging using MPI, OpenMP and pthreads on the Linux platform. It enables developers to debug applications that are running on hybrid clusters of x86-64 CPUs and Tesla GPU-based servers.

Numerical Analysis Packages: Significant advances in the use of CUDA-enabled GPUs have also been made in prominent numerical analysis and mathematical modeling packages such as MATLAB from Mathworks, Mathematica from Wolfram Research and LabVIEW from National Instruments.

CUDA Libraries: In addition, developers can take advantage of a rich set of CUDA-accelerated libraries available from NVIDIA and its partners including BLAS, FFT, LAPACK (EM Photonics CULA), MAGMA (ICL at the UTK), NVIDIA Performance Primitives (NPP), CUDA Vision Workbench (CVWB) and video and image processing libraries.

To accelerate the momentum of CUDA optimized tools and applications, customers can take advantage of worldwide training and consultancy services offered by a growing number of CUDA Consultants, such as Acceleware Corp., ANEO, CAPS, Elegant Mathematics, EM Photonics, Fixstars, GASS Ltd., HPC Project, Infosys, SagivTech, Stone Ridge Technology and Tech-X Corp.

The breadth of languages, APIs, libraries and other tools that are now supported by NVIDIA graphics processing units (GPUs) based on the CUDA parallel processing architecture represent the industry's most flexible and pervasive set of tools available for parallel computing today.



DV Hardware - Privacy statement
All logos and trademarks are property of their respective owner.
The comments are property of their posters, all the rest © 2002-2017 DM Media Group bvba