NVIDIA Updates CUDA Parallel Computing Platform
 SANTA
CLARA,
CA, Jan 27, 2012 - NVIDIA today released a new version of its CUDA parallel computing platform,
which will make it easier for computational biologists, chemists, physicists,
geophysicists, other researchers, and engineers to advance their simulations and
computational work by using GPUs.
The new NVIDIA CUDA parallel computing platform features three key
enhancements that make parallel programming with GPUs easier, more accessible
and faster. These include:
-
Re-designed Visual Profiler with automated performance
analysis, providing an easier path to application acceleration
-
New compiler, based on the widely-used LLVM open-source
compiler infrastructure, delivering up to 10 percent speed up in application
performance
-
Hundreds of new imaging and signal processing functions,
doubling the size of the NVIDIA Performance Primitives (NPP) library
"The new visual profiler is amazing," said Joshua Anderson,
lead developer of the HOOMD-blue open source molecular dynamics project. "With
just a few clicks, it performs an automated performance analysis of your
application, highlights likely problem areas, and then provides links to
best-practice suggestions on improving them. It makes it quick and easy for
virtually all developers to accelerate a broad range of applications."
"The LLVM complier gave me an almost immediate 10 percent performance speed
up, just by recompiling my existing real-time financial risk analysis code,"
said Gilles Civario, senior software architect at the Irish Centre for High-End
Computing. "I can only imagine the additional performance gains I can achieve
with additional tuning using the new CUDA release."
Among the new features of the latest CUDA parallel computing platform release
- available free of charge on the NVIDIA developer website. For further
information, click here.
New Visual Profiler - Easiest path to performance optimization
The new Visual Profiler makes it easy for developers at all experience levels
to optimize their code for maximum performance. Featuring automated performance
analysis and an expert guidance system that delivers step-by-step optimization
suggestions, the Visual Profiler identifies application performance bottlenecks
and recommends actions, with links to the optimization guides. Using the new
Visual Profiler, performance bottlenecks are easily identified and actionable.
LLVM Compiler - Instant 10 percent increase in application
performance
LLVM is a widely-used open-source compiler infrastructure featuring a modular
design that makes it easy to add support for new programming languages and
processor architectures. Using the new LLVM-based CUDA compiler, developers can
achieve up to 10 percent additional performance gains on existing
GPU-accelerated applications with a simple recompile. In addition, LLVM's
modular design allows third-party software tool developers to provide a custom
LLVM solution for non-NVIDIA processor architectures, enabling CUDA applications
to run across NVIDIA GPUs, as well as those from other vendors.
New Image, Signal Processing Library Functions - "Drop-in"
Acceleration with NPP Library
NVIDIA has doubled the size of its NPP library, with the addition of hundreds
of new image and signal processing functions. This enables virtually any
developer using image or signal processing algorithms to easily gain the benefit
of GPU acceleration, with the simple addition of library calls into their
application. The updated NPP library can be used for a wide variety of image and
signal processing algorithms, ranging from basic filtering to advanced
workflows.
About CUDA
CUDA is NVIDIA's parallel computing platform and programming model, which
enables dramatic increases in computing performance by harnessing the power of
GPUs. NVIDIA CUDA GPUs support all GPU computing programming models, APIs, and
languages, including CUDA C/C++/Fortran, OpenCL, and DirectCompute. More than
500 universities and institutions worldwide teach the CUDA programming model
within their curriculum. In addition, the CUDA parallel programming platform has
been downloaded more than 1.2 million times to date.
For more information on the NVIDIA CUDA parallel computing platform visit the
CUDA web site at www.nvidia.com/cuda.
For more NVIDIA news, company and product information, videos/images, and
other information, visit the NVIDIA newsroom.
About NVIDIA
NVIDIA (NASDAQ: NVDA) awakened the world to computer graphics when it
invented the GPU in 1999. Today, its processors power a broad range of products
from smart phones to supercomputers. NVIDIA's mobile processors are used in cell
phones, tablets and auto infotainment systems. PC gamers rely on GPUs to enjoy
spectacularly immersive worlds. Professionals use them to create visual effects
in movies and design everything from golf clubs to jumbo jets. And researchers
utilize GPUs to advance the frontiers of science with high-performance
computing. The company holds more than 2,200 patents worldwide, including ones
covering ideas essential to modern computing. For more information, see
www.nvidia.com.
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NVIDIA
website
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