Understanding GPU Inference Workloads [D]
Mirrored from r/MachineLearning for archival readability. Support the source by reading on the original site.
Hey everyone,
I have been looking into how people source compute for their Inference workloads (and in general). I wanted to understand some specific pain points here.
If you've used online services like runpod or vast.ai, your perspective is extremely valuable. Please share your experience in the comments here or by DMing me. I've also made a 2 minute survey form that I would really appreciate if you could fill out. DM me for the link.
Thank you!
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