This is the first article in a series that I will write about on the topic of parallel programming and CUDA. In this guide I will explain how to install CUDA 6.0 for Mac OS X. CUDA is a proprietary programming language developed by NVIDIA for GPU programming, and in the last few years it has become the standard for GPU computing. Migrating the discussion from the other thread, since you have the same graphics card I do, I'm curious what CUDA-Z shows for performance for you? In particular, does your 2017 MBP get better bandwidth? See my results attached. The web drivers are needed to detect and communicate with the GTX 1050, while the CUDA drivers are needed for CUDA. Welcome to the Geekbench CUDA Benchmark Chart. The data on this chart is calculated from Geekbench 5 results users have uploaded to the Geekbench Browser. To make sure the results accurately reflect the average performance of each GPU, the chart only includes GPUs with at least five unique results in the Geekbench Browser.
Cuda Z For Mac Os
This blog post describes how to install the CUDA Toolkit (i.e., thedevelopment tools, including shared libraries, the compiler, thenvidia visual profiler, the handytools/CUDA_Occupancy_Calculator.xls, and so on) on a Mac without anNVIDIA GPU.
Virtual mac for mac. Macs with an NVIDIA GPU are now a dying species, with the latestMacbook Pros having switched to AMD discrete graphics cards for thepast few years. This means that even if you install the CUDAdevelopment tools, you probably won’t be able to execute any CUDAcode.
However, there are a few reasons why this is useful:
SMBX has a tough time connecting to and staying connected to SMB shares hosted by Windows Server 2012 or higher servers. 
SMBX read speeds are pretty fast, but SMBX write speeds are 1/10th of what they should be.Some solutions are to force SMBX to use SMB 1, there are work arounds on the net. SMBX has major problems and causes OSX to have very poor networking skills. SMBX supports SMB 2, while the rest of the modern operation systems are already on 3.x or higher. 10.8 was still on SMB 1.
Development of code without having to access a remote machine. Ibasically work exclusively through an ssh connection to a linuxmachine from a mac laptop for my day-to-day work.
Use of CUDA’s GUI tools without suffering the lag of a remoteconnection. In particular, the NVIDIA Visual Profiler allows you toload the output of nvprof for analysis, allowing you to profile on aremote machine, but analyze locally. This is the number one reasonwhy I figured out how to do this.
For example, you can dump statistics like this with nvprof:
scp it to your local machine, then open it with
nvvp warp-ctc.nvprof. Thanks to this blog post for telling me about this.
Installation Steps
Download one of the disk images fromthe install site. Openit up. This will mount it under the directory /Volumes.
Then do:
Cuda Z For Mac Iso
Once it is done, your installation should sit in /Developer/NVIDIA/CUDA-*.*/.
To be clear here,specifically you are installing only the “toolkit”,which doesn’t contain the drivers. Hopefully this dispells the myththat you need an NVIDIA GPU to even have the CUDA developmentlibraries on a Mac.