The Missing Nvidia GPU Glossary (modal.com)

Screenshot of modal.com: The Missing Nvidia GPU Glossary

First screen, captured 1 year ago.

Looks similar

Screenshot of libc.llvm.org: Using Libc for GPUs

Using Libc for GPUs (libc.llvm.org)

177 points by hochmartinez 1 year ago | 76 comments

Screenshot of ollama.com: Gemma3 – The current strongest model that fits on a single GPU

Gemma3 – The current strongest model that fits on a single GPU (ollama.com)

212 points by brylie 1 year ago | 86 comments

Screenshot of gpuhammer.com: GPUHammer: Rowhammer attacks on GPU memories are practical

GPUHammer: Rowhammer attacks on GPU memories are practical (gpuhammer.com)

260 points by jonbaer 1 year ago | 89 comments

Screenshot of efraingaray.com: TabPFN and TabICL vs. tuned XGBoost: the model that doesn't train won 14/14

TabPFN and TabICL vs. tuned XGBoost: the model that doesn't train won 14/14 (efraingaray.com)

21 points by EfrainGaray 28 days ago | 9 comments

Blog post benchmarking TabPFN and TabICL foundation models against tuned XGBoost on fourteen tabular datasets, finding the no-training models won all fourteen.

tabpfn tabicl xgboost tabular-data

Screenshot of github.com: INapGPU: Text-mode graphics card, using only TTL gates

INapGPU: Text-mode graphics card, using only TTL gates (github.com)

76 points by userbinator 1 year ago | 11 comments

Screenshot of mlc.ai: Modern GPU Programming for MLSys

Modern GPU Programming for MLSys (mlc.ai)

68 points by crowwork 4 months ago | 15 comments

Looks similar

Using Libc for GPUs(libc.llvm.org)

Gemma3 – The current strongest model that fits on a single GPU(ollama.com)

GPUHammer: Rowhammer attacks on GPU memories are practical(gpuhammer.com)

TabPFN and TabICL vs. tuned XGBoost: the model that doesn't train won 14/14(efraingaray.com)

INapGPU: Text-mode graphics card, using only TTL gates(github.com)

Modern GPU Programming for MLSys(mlc.ai)