CUDA, every mention

Multi-GPU Kernels, Intelligence per Watt, Heterogeneous Inference, and More | YC Paper Club · Y Combinator Jul 29, 2026 · 9 mentions

• ▶ 1:06 Francois Chaubard You can't do that with inference, and there's so many things like that that we'll talk about, and there's so much juice left to squeeze on the CUDA side, on the kernel side,
• ▶ 7:30 Stuart (Stu) Um, one quick note before I begin, um, the final deliverable of this paper is a CUDA framework that we refer to as parallel kittens, but the goal of today's talk is not to promote my open source library, but rather to convey the set of…
• ▶ 19:14 Stuart (Stu) So Parallel Kittens builds on all the trade-offs and principles that we discussed, and it's a highly opinionated set of CUDA programming primitives that extends Thunder Kittens, which is one of our previous works for single GPU kernels.
• ▶ 33:03 unnamed speaker Ultimately, these dispatch down to individual CUDA kernels that may or may not be very fast on modern hardware, which is why we get programming languages like Triton, which are a tile-based. 2 times in the scene
• ▶ 34:44 unnamed speaker And at least, like, for this archetype of people that just want state-of-the-art perf, as far as I can tell, like, they really prefer, like, CUDA, and it was only when we were doing lots of gem-related problems that people loved using…
• ▶ 35:32 unnamed speaker I've never written an open and CUDA book before.
• ▶ 37:23 unnamed speaker I'm gonna make you, if you've never written a CUDA kernel before, you're gonna do one with me right now.
• ▶ 1:14:36 unnamed speaker Like, I see a lot of programming language systems are kind of trending towards, okay, it's still the Cuda programming model, but it's Python syntax on top, which is great, like, simplifies things, easier to look at, but it doesn't actually…