OS X 10.12.6 was working great for me…until I wanted to run tensorflow on GPU. OS X 10.13 didn’t help.

Unfortunately tensorflow isn’t Mac friendly, because “As of version 1.2, TensorFlow no longer provides GPU support on Mac OS X.”. I don’t even understand what that means since you can always build from source assuming NVIDIA provides CUDA support for Mac. But I did get a working build with tensorflow 1.1 running with CUDA 8 on my GTX 1080 GPU (and Xcode 7.3).

However, running GPU intensive programs would occasionally crash my computer! After spending hours trying to extract some crash logs (they were not in Console), I found that I was getting a kernel panic, and I couldn’t figure out how to fix it.

So I naively decided to update my Hackintosh to OS X 10.13 High Sierra, hoping to find more stable GPU performance. I followed this tutorial to update from 10.12.6 (thanks kgp); the biggest snag was that KernelPM in Kernel and Kext Patches should’ve been set to true, and the Install USB would not boot from the USB 3.0 port! It only worked in the USB 2.0 port…

In any case, NVIDIA released driver 378. for OS X 10.13 as of October 9th, with no support for the CUDA Toolkit. I quote, “A CUDA driver which supports macOS High Sierra 10.13 will be available at a later date.” So I can’t even use tensorflow with GPU on Mac. Apple, please get your act together.

So my solution to not being able to run tensorflow GPU on a Mac:

It’s a pretty sweet build!

If you’re interested, here are some read/write stats on the NVMe using this tutorial:

> sync; dd if=/dev/zero of=tempfile bs=1M count=1024; sync
1024+0 records in
1024+0 records out
1073741824 bytes (1.1 GB, 1.0 GiB) copied, 0.446358 s, 2.4 GB/s

> dd if=tempfile of=/dev/null bs=1M count=1024
1024+0 records in
1024+0 records out
1073741824 bytes (1.1 GB, 1.0 GiB) copied, 0.375208 s, 2.9 GB/s

Now that’s pretty fast!

Some other niceties I set up:

  • rclone backups to my Google Drive account
  • Time Machine backups to an internal 1TB HDD
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Baruch Tabanpour



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