一个工程师复盘自己的神预言：megakernels和推理ASIC都没戏，GPU调优会被RL接管，NVIDIA靠软件和HBM赢。
作者在 @swyx 播客上复盘两个月前的争议言论，坚持认为 megakernels 已死。他的理由是内核复杂度太高，没有推理服务商会在生产中用 67k 行手工融合前向传播内核。他认为 GPU 内核优化是最适合强化学习的任务，AI 代理用 ncu CLI 和 MCP 就能自动调优。他还预测数据中心 Transformer 推理 ASIC 因架构未收敛而失败，NVIDIA 的护城河在于 HBM 容量带宽和软件工具链。
"With megakernels, honestly I'm very bearish. [Megakernels] was a good research direction and it see...
"With megakernels, honestly I'm very bearish. [Megakernels] was a good research direction and it seems very... intuitively and theoretically, it's nice. [However], the kernel complexity itself makes it very difficult to write a very optimized megakernel." Your browser does not support the video tag. 🔗 View on Twitter ali @waterloo_intern two weeks ago i went on @swyx 's pod and said some things that i... should not have said. a lot has happened since then, i owe you all an apology. i'm sorry that i was right about every single thing. a) re megakernels are dead why are megakernels useful? you spend two months writing a kernel to save time on launch overhead and poor inter-kernel overlap. you had PDL but then people said it wasn't perfect, that you could still get some marginal gains due to straggler CTAs and therefore- wait, sorry, I forgot, Rubin fixes that (kernel two needs 10 CTAs and kernel one has seven finished and three straggling, kernel two launches seven of its CTAs). given a long enough timeline, it all evens out. no serious inference provider is using a 67k loc hand-fused forward pass kernel in production, and the teams doing that are doing so out of pure research. dead. b) re ASICs are dead i'm sorry. to be specific: data-center transformer-inference ASIC companies (not naming any) who etched the arch into silicon have bet on architectural convergence. read kimi's architecture. read deepseek. qwen. we did not converge, and probably will not. dead. c) re gpu kernel dev is dead this one kind of hurts because it is (was) my job. gpu kernel optimization is the single most RL-able task in existence correct=check_correctness(kernel, shape) for shape in shapes if all(correct): time(kernel) give an agent ncu cli and an mcp with nvidia's tribal knowledge and it's done. dead. d) re NVIDIA is scared of AMD humans hate programming AMD. i'm sorry. it's just true. fine taking a performance hit as long as i don't have to touch rocm or a programming paradigm that says a warp is 64 threads (wtf?)...but an agent does not... so assuming software no longer moat, HBM capacity and bandwidth matter, and currently on perf / price they're goated. 'bUt NvIdIa iS gOaTeD oN hArDwArE sOfTwArE cOdEsIgN' and that's the new moat. watch how much tooling they open source to get kernel devs on nvidia. apologies all. 🔗 View Quoted Tweet 💬 1 🔄 0 ❤️ 0 👀 107 📊 1 ⚡