we launched the most comprehensive ai performance engineering repo in the world
This is a dev post classified by Jev as AI dev tools (a free resource), kept by the Dev Radar because it carries real work, not commentary.
we launched the most comprehensive ai performance engineering repo in the world now we'll be posting every single resource this is Wafer's ai performance engineering series save this to keep up with the series. links in thread 🧵 part 3: "Intro to CUDA C++" from NVIDIA's CUDA Programming Guide. NVIDIA covers the execution model, memory movement, and correctness checks behind CUDA programs: - kernel launches, grid dimensions, and the organization of threads into blocks. - thread indexing and work assignment, including bounds checks for inputs that aren't multiples of the block size.
Posted by wafer (11.7k followers) 1 h ago · 44 likes · 3k views · view the original post on X. Kept by the Dev Radar as AI dev tools.
More dev work like this
- Did you already know, that you can interact via CLI with the apple foundation models? — @haukejung
- A new benchmark called JevBench just dropped. — @rohanpaul_ai
- Stop burning turns rewriting vague AI prompts — @DanKornas
- I WOKE UP TO MONEY — @michael_chomsky
- Structures a Claude Code session into a game studio with 49 specialized AI agents and 73… — @tom_doerr
- Jev is cool. So is it's OSS companion, Laya. — @BenjDicken
- I think we’re looking for this — @vaibcode
- When a hard coding decision needs a second opinion, don’t settle for one model. — @DanKornas
Every post is read and classified by Jev (TypeSafe): what it is, which market it belongs to, and whether the link is a real tool. 15.1k posts from 4.7k X accounts over the last 21 days, 1.7k tools, 12 markets. Collected every 5 minutes, fully re-ranked every hour — last update 2026-09-19 22:37 UTC. Full method.