NVIDIA CUDA Toolkit 2.2 Released
 SANTA
CLARA, CA, May 12, 2009 - NVIDIA announced today it has released version 2.2
of the CUDA Toolkit and SDK for GPU Computing. This latest release supports
several significant new features that deliver a major leap forward in
getting the most performance out of NVIDIA’s massively parallel CUDA-enabled
GPUs. In addition, version 2.2 of the CUDA Toolkit includes support for
Windows 7, the upcoming OS from Microsoft that embraces GPU Computing.
Additional new features in CUDA Toolkit 2.2 include:
- Visual Profiler for the GPU
The most common step in tuning application performance is profiling
the application and then modifying the code. The CUDA Visual Profiler is
a graphical tool that enables the profiling of C applications running on
the GPU. This latest release of the CUDA Visual Profiler includes
metrics for memory transactions, giving developers visibility into one
of the most important areas they can tune to get better performance.
- Improved OpenGL Interop
Delivers improved performance for Medical Imaging and other OpenGL
applications running on Quadro GPUs when computing with CUDA and
rendering OpenGL graphics functions are performed on different GPUs.
- Texture from Pitch Linear Memory
Delivers up to 2x bandwidth savings for video processing
applications.
- Zero-copy
Enables streaming media, video transcoding, image processing and
signal processing applications to realize significant performance
improvements by allowing CUDA functions to read and write directly from
pinned system memory. This reduces the frequency and amount of data
copied back and forth between GPU and CPU memory. Supported on MCP7x and
GT200 and later GPUs.
- Pinned Shared System
Enables applications that use multiple GPUs to achieve better
performance and use less total system memory by allowing multiple GPUs
to access the same data in system memory. Typical multi-GPU systems
include Tesla servers, Tesla Personal Supercomputers, workstations using
QuadroPlex deskside units and consumer systems with multiple GPUs.
- Asynchronous memcopy on Vista
Allows applications to realize significant performance improvements
by copying memory asynchronously. This feature was already available on
other supported platforms but is now available on Vista.
- Hardware Debugger for the GPU
Developers can now use a hardware level debugger on CUDA-enabled
GPUs that offers the simplicity of the popular open-source GDB debugger
yet enables a developer to easily debug a program that is running 1000s
of threads on the GPU. This CUDA GDB debugger for Linux has all the
features required to debug directly on the GPU, including the ability to
set breakpoints, watch variables, inspect state, etc.
- Exclusive Device Mode
This system configuration option allows an application to get
exclusive use of a GPU, guaranteeing that 100% of the processing power
and memory of the GPU will be dedicated to that application. Multiple
applications can still be run concurrently on the system, but only one
application can make use of each GPU at a time. This configuration is
particularly useful on Tesla cluster systems where large applications
may require dedicated use of one or more GPUs on each node of a Linux
cluster.
Developers can download the latest CUDA Toolkit, SDK, and drivers now at
www.nvidia.com/cuda
About NVIDIA
NVIDIA (Nasdaq: NVDA) is the world leader in visual computing
technologies and the inventor of the GPU, a high-performance processor which
generates breathtaking, interactive graphics on workstations, personal
computers, game consoles, and mobile devices. NVIDIA serves the
entertainment and consumer market with its GeForce graphics products, the
professional design and visualization market with its Quadro graphics
products, and the high-performance computing market with its Tesla™
computing solutions products. NVIDIA is headquartered in Santa Clara, Calif.
and has offices throughout Asia, Europe, and the Americas.
For more information, visit www.nvidia.com.
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Oct 2 - ORNL to Use NVIDIA Fermi Architecture for Supercomputer
Aug 04 - NVIDIA Launches Interactive Ray Tracing Engine
Jul 15 - NVIDIA Offers Optimized Quadro Drivers for AutoCAD 2010
May 12 - NVIDIA CUDA Toolkit 2.2 Released
May 7 - NVIDIA Tesla GPUs Available in Dell Workstations
Apr 21 - NVIDIA Quadro FX 4800 GPU Supports Mac
Apr 3 - NVIDIA Names Harvard University 'CUDA Center Of Excellence'
Mar 31 - NVIDIA Introduces Quadro Pro GPU Product Line
Mar 31 - NVIDIA SLI Multi-OS Available for Graphics Workstation
Mar 3 - NVIDIA Releases GeForce Graphics Drivers for Windows 7 Beta
Feb 27 - NVIDIA Names Bob Sherbin to Head Corporate Communications
Jan 29 - Stanford's Bill Dally Joins NVIDIA as VP Research
Jan 14 - NVIDIA Expects Q4 Revenue Down 40-50%
Dec 3 - NVIDIA Releases Quadro FX 4800 Graphics Card for MCAD
Nov 11 - NVIDIA Unveils Quadro Plex 2200 S4 VCS 3D Accelerator
Sep 16 - NVIDIA Founder Huang to Donate $30M to Stanford University
Aug 26 - NVIDIA, CGSociety Announces 3rd NVArt Contest Winners
Aug 15 - NVIDIA Offers Free OpenGL 3.0 Beta Drivers for 3D Graphics
Aug 7 - NVIDIA Announces NVISION 08 Keynote Lineup
Jul 30 - Dassault CEO Bernard Charles to Present at NVISION 08
Source: Material used in press releases is often supplied by external
sources and used as is.
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