Nvidia CUDA is a parallel computing platform using Nvidia graphics card hardware which allows the developers and security related humans to use a CUDA-enabled graphics processing unit (GPU) for general purpose processing which is called GPGPU (General Purpose computing on Graphics Processing Units). CUDA platform is a software layer to give access to the GPU’s virtual instruction set and parallel computational elements. CUDA is designed to work with C, C++, C#, Fortran, Java, Python etc. Usually the intelligent humans use CUDA for testing security of own and others servers. Officially CUDA has usage for Bioinformatics, Computational Chemistry, Computational Finance, Computational Fluid Dynamics, Computational Structural Mechanics, Data Science, Defense, Electronic Design Automation, Imaging & Computer Vision, Machine Learning, Medical Imaging, Numerical Analytics and so on. Here is a detailed Nvidia CUDA tool installation guide for parallel computing for MacOS X. It is difficult to install all the stuffs & make it working.
Probably you heard about tensorflow. After installing these packages, you can use tat software package.
Kindly invest some time to prepare, install and configure your system. You need some modern internet connection as total size of download will go over 2 GB. Here is an old official PDF which has minimal importance for bash configuration :
Here is Nvidia CUDA official installation guide for MacOS x :
Nvidia CUDA Tool Installation Guide For Parallel Computing : MacOS X
First you need to check whether your Mac has graphics card supporting Nvidia CUDA and get details of which version of CUDA will be supported. Click on the Apple icon > Click “About this Mac” > Click “System Report” > Click “Graphics/Display” > Click “Nvidia…” > Copy the Nvidia graphics card model number. For Mid 2012 MacBook Pro 15″, it is NVIDIA GeForce GT 650M. And total details is :
Chipset Model:NVIDIA GeForce GT 650M
PCIe Lane Width:x8
VRAM (Total):512 MB
Automatic Graphics Switching:Supported
Now, perform a Google search with key phrase with that model with CUDA like “NVIDIA GeForce GT 650M CUDA” in our example and land to Nvidia’s official webpage against that model, in our example it is :
If you fail in the above way, go to this webpage :
Click “GeForce Notebook Products”, a list will appear (the webpage’s exact words to click changes with their launch of new products). That same webpage will appear.
You can browse the other tabs to get more info. On Wikipedia’s this list :
NVIDIA GeForce GT 650M supports CUDA 3.0, on the same webpage of Wikipedia, you will get version features and specifications. CUDA 3.0 is not outdated and proves that 5 years old MacBook Pro is not really old. Now download and install Xcode from the App Store to latest :
After installing latest Xcode, open Terminal or iTerm and install the developer tools :
Restart your Mac. Now go to :
There will be big box with writings like “Select your platform below to download the toolkit. Select Target Platform. Click on the green buttons that describe your target platform. Only supported platforms will be shown.”
You know how to select. That size of download is 1.4 GB. You’ll see links under “Get Started”. If you get in to trouble, use them. Install it and follow what is written from point 3.2 :
Thats it. You could install by :
brew cask install cuda
But we have reasons to avoid that easy way.Tagged With the macOS installation couldnt be completed