CUDA is a parallel computing platform and programming model that enables dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU).
Since its introduction in 2006, CUDA has been widely deployed through thousands of applications and published research papers, and supported by an installed base of over 300 million CUDA-enabled GPUs in notebooks, workstations, compute clusters and supercomputers. Learn more about GPU-accelerated applications available for astronomy, biology, chemistry, physics, data mining, manufacturing, finance, and more on the software solutions page.
Software developers, scientists and researchers can add support for GPU acceleration in their own applications using one of three simple approaches:
Drop in a GPU-accelerated library to replace or augment CPU-only libraries such as MKL BLAS, IPP, FFTW and other widely-used libraries
Automatically parallelize loops in Fortran or C code using OpenACC directives for accelerators
Develop custom parallel algorithms and libraries using a familiar programming language such as C, C++, C#, Fortran, Java, Python, etc.
To download and install the drivers, follow the steps below:
Step 1: Review the NVIDIA Software License. Check terms and conditions checkbox to allow driver download. You will need to accept this license prior to downloading any files.
Step 2: Download the Driver File.
Step 3: Install
Note: Quadro FX for Mac or GeForce for Mac must be installed prior to CUDA 5.5.25 installation
Double click on downloaded file
Click Continue on the CUDA Installer Welcome screen
Click Continue after you read the License Agreement and then click Agree
Click Install on the Standard Install Screen. You will be required to enter an Administrator password
Once you see the Successful Installation screen, your install is complete. No restart is required
Supports all NVIDA products available on Mac hardware.