CUDA Toolkit For Developers
The CUDA application software download free Windows enables you to deploy GPU computing applications with ease. The package includes libraries, debugging and optimization tools, a compiler, and documentation. It supports all generations of NVIDIA GPUs, but performs best on the latest Tesla GPUs, such as the V100 which can accelerate deep learning training workloads by 3x and signal processing by 2x.
CUDA applications execute on the GPU using parallel execution units, called threads. Threads are lightweight execution units that can be grouped into grids for parallel processing. The CUDA programming model is designed to take advantage of the compute capabilities of the GPU by optimizing threads for maximum performance. CUDA-enabled applications run faster on a GPU than on the CPU and can scale across multiple GPUs to achieve even greater performance gains.
Developers can optimize the performance of their applications by using a suite of performance analysis and debugging tools, such as Nvidia Visual Profiler and CUDA Debugger. These tools help developers identify bottlenecks and fine-tune the application code to maximize performance.
With the CUDA 11.5 release, NVCC now offers the option to use -arch=native to let NVCC select the correct target architecture for compiled CUDA device code based on the NVIDIA GPU installed in the system. -arch=native also provides a way for developers to test applications on different NVIDIA GPUs without having to install them.
CUDA 6.0 introduces the new NPP library, which provides over 500 image and signal processing primitives for BGR/YUV conversion, color transformations including trilinear interpolation and optimized Huffman coding for JPEG, filter median routines, error metric computations, and miscellaneous pixel and color operations. In addition, NPP adds support for per-client priority mapping at runtime for CUDA Multi-Process Service (MPS).