NVIDIA is likely citing 1 PFlops at FP 4 sparse (they did this for GB200), so that is 128 TFlops BF16 dense, or 2/3 of what RTX 4090 is capable of. I would put the memory bandwidth at 546 GBps, using the same 512 bit…
Yep I have seen this paper before, and thank you for linking it here for reference. My personal opinion is that compared to single epoch scaling laws, we still need more evidence and literature on effects of multiple…
What they missed is that current scaling laws (OpenAI, Deepmind Chinchilla) are based on the assumption that the model is trained for one epoch. This essentially means that in order to scale compute, you will have to…
My experience is that < 500M models are pretty useful when fine-tuned on traditional NLP tasks, such as text classification and sentence/token level labeling. A modern LM with a 32K context window size could be a nice…
Checked your numbers in another thread - excellent breakdown. Thanks for the clarification. I did not read the original anandtech post so I did not realize the 512GBps already refers to the full-duplex bandwidth. You…
NVLink advertises combined bandwidth in both direction, so the 1800 GBps NVLink on Blackwell is actually 900 GBps for everyone else. PCIe can also do multi-node direct transfer via PCIe switches and has been already…
Depends. NVLink advertises bidirectional bandwidth, whereas PCIe and standard networking calculate bandwidth in a single direction. So a 1800 GBps NVLink is actually 900 GBps in PCIe and standarding networking terms.…
Unfortunately GZIP won't beat LLMs for text classification. The research you cited is just poorly done science that has been widely debunked. The original paper compared top-2 accuracy of GZIP with top-1 accuracy with…
NVIDIA is likely citing 1 PFlops at FP 4 sparse (they did this for GB200), so that is 128 TFlops BF16 dense, or 2/3 of what RTX 4090 is capable of. I would put the memory bandwidth at 546 GBps, using the same 512 bit…
Yep I have seen this paper before, and thank you for linking it here for reference. My personal opinion is that compared to single epoch scaling laws, we still need more evidence and literature on effects of multiple…
What they missed is that current scaling laws (OpenAI, Deepmind Chinchilla) are based on the assumption that the model is trained for one epoch. This essentially means that in order to scale compute, you will have to…
My experience is that < 500M models are pretty useful when fine-tuned on traditional NLP tasks, such as text classification and sentence/token level labeling. A modern LM with a 32K context window size could be a nice…
Checked your numbers in another thread - excellent breakdown. Thanks for the clarification. I did not read the original anandtech post so I did not realize the 512GBps already refers to the full-duplex bandwidth. You…
NVLink advertises combined bandwidth in both direction, so the 1800 GBps NVLink on Blackwell is actually 900 GBps for everyone else. PCIe can also do multi-node direct transfer via PCIe switches and has been already…
Depends. NVLink advertises bidirectional bandwidth, whereas PCIe and standard networking calculate bandwidth in a single direction. So a 1800 GBps NVLink is actually 900 GBps in PCIe and standarding networking terms.…
Unfortunately GZIP won't beat LLMs for text classification. The research you cited is just poorly done science that has been widely debunked. The original paper compared top-2 accuracy of GZIP with top-1 accuracy with…