First screen, captured .
Looks similar
Meta's GB{2,3}00 Cluster(engineering.fb.com)
75 points by stokedmartin | 31 comments
Engineering at Meta blog post describing Prometheus, Meta's gigawatt-scale AI supercluster and the data center and networking work behind it.
Meta’s renewed commitment to jemalloc(engineering.fb.com)
495 points by hahahacorn | 226 comments
Engineering at Meta blog post announcing Meta's renewed investment in and commitment to maintaining the open-source jemalloc memory allocator.
Meta's open AI hardware vision(engineering.fb.com)
198 points by GavCo | 110 comments
Related stories
GPUs Go Brrr(hazyresearch.stanford.edu)
1056 points by nmstoker | 243 comments
Stanford Hazy Research blog post on what GPU hardware wants for efficient AI kernels, introducing the ThunderKittens CUDA kernel library.
Gemma 3 QAT Models: Bringing AI to Consumer GPUs(developers.googleblog.com)
571 points by emrah | 259 comments
Google Developers Blog post announcing Gemma 3 models trained with quantization-aware training so they can run on consumer GPUs.
Nvidia announces native GPU programming in Rust(developer.nvidia.com)
898 points by nonmaskable | 354 comments
NVIDIA Technical Blog post introducing CUDA Rust, describing two approaches for writing GPU kernels natively in Rust.
We were wrong about GPUs(fly.io)
834 points by mxstbr | 529 comments
Fly.io blog post reflecting on how the company's bet on offering GPU machines to developers did not pan out as expected.
What every developer should know about GPU computing(codeconfessions.substack.com)
422 points by Anon84 | 149 comments
A Substack primer by Abhinav Upadhyay explaining GPU architecture and computing concepts for software developers familiar mainly with CPUs.
The GPU, not the TPM, is the root of hardware DRM(mjg59.dreamwidth.org)
399 points by DvdGiessen | 408 comments
Blog post by Matthew Garrett arguing that GPUs, not TPMs, are the real root of hardware DRM; the capture shows a Dreamwidth captcha page instead.