u/prof_mistake

Hey everyone,

I’ve started trying to learn about Apple's M4 GPU architecture, but I'm hitting a wall due to the lack of deep-dive resources.

The main issue is finding a solid guide that breaks down the actual architecture of the M4 chips (compute unit counts, how they are arranged, etc.). On top of that, they don't map cleanly to CUDA at the architectural level.

I could use the Colab GPU, if I ignore the pain that comes with it. I own a Mac, so that would be easier.

The dilemma is that the Metal ecosystem is pretty niche, even though I'm highly interested in it. Because information is so scarce, the only real way to learn and optimize kernels seems to be taking a CUDA guide and mapping those techniques over to Metal. I feel like this strategy would work a lot better if I were actually proficient in CUDA first.

For context, I'm somewhere just above a beginner. I've taken a CUDA university course and worked through the Programming Massively Parallel Processors (PMPP) book, so I have the basics down. For the course project, I built a tiny replica of torch using the techniques from the book only (no tensor cores or anything)

Which approach makes more sense here?

I would highly appreciate help on this.

I'm at a REU program. My advisor told me to meet professors and see what other people are doing. Unfortunately, the lab I work at is mostly empty (maybe because everyone WfH or it's summer).

Anyway, I thought I could search up faculty profiles and reach out to them through email -- introducing myself, telling them what I've done, and why I've reached out to them etc. are doing. However, I have never done this before for solely networking purposes. Hence, My questions:

• I don't know if that's a good idea.
• I'm not sure what I would even say to them. I can't offer to work with them because I'm already working with my professor so I don't know.

I would highly appreciate any advice regarding this.