NVIDIA's CUDA Platform Makes Parallel Computing with GPUs Easier For Engineers
NVIDIA® CUDA® is the platform based on parallel computing that creates voluminous increases in computing performance using the power of GPUs and more than a million downloads of this platform proves that it is being used widely. #-Link-Snipped-# GPUs support all GPU computing programming models, APIs, and languages, including CUDA C/C++/Fortran, OpenCL, and DirectCompute. First unveiled in 2006, CUDA was the world's first solution for general-computing on GPUs. Now, a new version of CUDA is released by Nvidia making it easy for engineers to advance their simulations and computational work.
![[IMG]](proxy.php?image=http%3A%2F%2Fwww.crazyengineers.com%2Fwp-content%2Fuploads%2F2012%2F02%2Fimage004.png&hash=d4fc89db3202f234d02a2274df0fd8cf)
Among the new feature there are three prime enhancements. Firstly, there is a re-designed Visual Profiler with automated performance analysis making application acceleration an easy task. This all new visual profiler gets you the performance analysis of your application after only a few clicks and highlights the areas that can be improved and suggests best-practices using the expert guidance system to be used to tackle the problems.
Secondly, developers have a boon to get a completely new compiler, based on the widely-used #-Link-Snipped-# infrastructure, which has increased the application performance speed by 10 percent. LLVM has a modular design allowing third-party software tool developers to provide a custom LLVM solution for non-NVIDIA processor architectures. Thus, CUDA applications can run across GPUs not only from NVIDIA, but from other vendors also.
Last but not the least, we have double-sized NPP (NVIDIA Performance Primitives) library with hundreds of new imaging and signal processing functions, be it basic filtering or advanced workflows. For more information on the NVIDIA CUDA parallel computing platform visit the CUDA website at <span style="text-decoration: underline;">#-Link-Snipped-#.</span>
Among the new feature there are three prime enhancements. Firstly, there is a re-designed Visual Profiler with automated performance analysis making application acceleration an easy task. This all new visual profiler gets you the performance analysis of your application after only a few clicks and highlights the areas that can be improved and suggests best-practices using the expert guidance system to be used to tackle the problems.
Secondly, developers have a boon to get a completely new compiler, based on the widely-used #-Link-Snipped-# infrastructure, which has increased the application performance speed by 10 percent. LLVM has a modular design allowing third-party software tool developers to provide a custom LLVM solution for non-NVIDIA processor architectures. Thus, CUDA applications can run across GPUs not only from NVIDIA, but from other vendors also.
Last but not the least, we have double-sized NPP (NVIDIA Performance Primitives) library with hundreds of new imaging and signal processing functions, be it basic filtering or advanced workflows. For more information on the NVIDIA CUDA parallel computing platform visit the CUDA website at <span style="text-decoration: underline;">#-Link-Snipped-#.</span>
0