71–80 of 260 posts
https://www.merriam-webster.com/dictionary/gaudy
Honestly, I thought the same thing upon reading the name. I'm aware of the reference to Antoni Gaudí, but having the name sound so close to gaudy seems a bit unfortunate. Surely they must've had better options? Then again I don't know how these sorts of names get decided anymore.
This is a bit snarky — but will Intel actually keep this product line alive for more than a few years? Having been bitten by building products around some of their non-x86 offerings where they killed good IP off and then failed to support it… I’m skeptical. I truly do hope it is successful so we can have some alternative accelerators.
Earlier quoted context omitted.
[flagged]
Effectively everyone that has attempted to use AMD hardware for ML comes away with these opinions, the main difference is how angrily they express it.
I find it hard to believe "everyone" comes away with these opinions.
https://www.evp.cloud/post/diving-deeper-insights-from-our-l...
Earlier quoted context omitted.
Does it not work for them? Where can I learn why?
Just go have a look around Github issues in their ROCm repositories on Github. A few months back the top excuse re: AMD was that we're not supposed to use their "consumer" cards, however the datacenter stuff is kosher. Well, guess what, we have purchased their datacenter card, MI50, and it's similarly screwed. Too many bugs in the kernel, kernel crashes, hangs, and the ROCm code is buggy / incomplete. When it works,…
Earlier quoted context omitted.
Which would be impressive had it _actually_ worked for ML workloads.
There's a number of scaled AMD deployments, including Lamini ( https://www.lamini.ai/blog/lamini-amd-paving-the-road-to-gpu... ) specifically for LLM's. There's also a number of HPC configurations, including the world's largest publicly disclosed supercomputer (Frontier) and Europe's largest supercomputer (LUMI) running on MI250x. Multiple teams have trained models on those HPC setups too. Do you have any more eviden…
They don't. Loud voices parroting George, with nothing to back it up.
Here are another couple good links:
https://www.evp.cloud/post/diving-deeper-insights-from-our-l...
https://www.databricks.com/blog/training-llms-scale-amd-mi25...
A bit surprised that they're using HBM2e, which is what Nvidia A100 (80GB) used back in 2020. But Intel is using 8 stacks here, so Gaudi 3 achieves comparable total bandwidth (3.7TB/s) to H100 (3.4TB/s) which uses 5 stacks of HBM3. Hopefully the older HBM has better supply - HBM3 is hard to get right now! The Gaudi 3 multi-chip package also looks interesting. I see 2 central compute dies, 8 HBM die stacks, and then 6…
> A bit surprised that they're using HBM2e, which is what Nvidia A100 (80GB) used back in 2020. This is one of the secret recipes of Intel. They can use older tech and push it a little further to catch/surpass current gen tech until current gen becomes easier/cheaper to produce/acquire/integrate. They have done it with their first quad core processors by merging two dual core processors (Q6xxx series), or by creating…
Earlier quoted context omitted.
Effectively everyone that has attempted to use AMD hardware for ML comes away with these opinions, the main difference is how angrily they express it.
So who's buying all the MI300s? Groq seems to be fine with AMD.
We are. Just closed additional funding and getting quotes now.
Earlier quoted context omitted.
> A bit surprised that they're using HBM2e, which is what Nvidia A100 (80GB) used back in 2020. This is one of the secret recipes of Intel. They can use older tech and push it a little further to catch/surpass current gen tech until current gen becomes easier/cheaper to produce/acquire/integrate. They have done it with their first quad core processors by merging two dual core processors (Q6xxx series), or by creating…
Interesting. Would you say this means Intel is "back," or just not completely dead?