CARELESS on MacOS GPU/Metal

Software Careless
1

Is it possible to use the TensorFlow Apple SIlicon GPU implementation for mac with CARELESS?

2

@aaronfinke, Apple has a plugin that makes the Apple Silicon GPU available to TensorFlow. It’s not something I have in my tests or documentation, but I’m happy to support it if it’s a feature that users want. I have to say though that I just tried it on an M3 Pro. While TensorFlow picks up and uses the GPU just fine, it’s actually slower with the GPU than without (~8 iterations / s with vs 15 without GPU on my hewl ssad benchmark). You can make a new conda env to try it out:

conda create -yn metal python=3.12
conda activate metal
pip install -u pip
pip install careless
pip install tensorflow-metal

You can confirm it worked by running careless devices:

(metal) PC103400:hewl_ssad kmdalton$ careless devices
Careless version 0.5.4
###############################################
# TensorFlow can access the following devices #
###############################################
 - CPU: /physical_device:CPU:0
 - GPU: /physical_device:GPU:0

You should see a GPU device listed if everything went to plan.

3

Thanks, I got it working too with some noodling. I also found the GPU run to be slower than the CPU (same Mac specs as you). I was hoping for some performance benefit… c’est la vie.

4

Yeah I’m honestly not sure whether to expect it to run faster on metal or not. I don’t know enough about Apple CPUs. Sorry it wasn’t a big performance win, but thanks for trying it out!