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On 2026-08-06 Ali (@waterloo_intern) asserts "megakernels are dead"

2026-08-06 · 23:14 UTC ·@swyx ·2 min read

Brief

Ali (@waterloo_intern) argues that three long-term ML infra theses are "dead" (post on 2026-08-06). He says megakernels are obsolete — no serious inference provider runs a 67k-line hand-fused forward pass and Rubin-like CTA scheduling removes benefits. He claims etched transformer-ASIC bets failed as architectures diverged (mentions Kimi, Deepseek, Qwen), and kernel tuning is automatable with agents using ncu and MCP.

Why it matters

On 2026-08-06 Ali (@waterloo_intern) asserts "megakernels are dead": no serious inference provider runs a 67k-line hand-fused forward-pass kernel in production and Rubin-style CTA scheduling resolves straggler issues (example: kernel two needs 10 CTAs; kernel one has seven finished and three straggling → kernel two launches seven CTAs).

Key details

  • Ali asserts "etched ASICs are dead" for data-center transformer inference: firms that etched architectures into silicon bet on convergence (mentions Kimi, Deepseek, Qwen); he notes reports that AMD bought Taalas and that Etched was valued at $10B by SK Hynix and TSMC, but architectural divergence sank those bets.
  • Ali claims GPU kernel development is automatable and thus "dead" as a human job: kernel optimization is RL-able (pseudo-workflow: check correctness across shapes then time), an agent with ncu CLI plus Nvidia's MCP/tribal knowledge can do it; he adds humans "hate programming AMD" (warp=64 complaint) while NVIDIA's HBM capacity/bandwidth and potential open-sourcing of tooling preserve its hardware/software advantage.
Source evidence

man @waterloo_intern theses keep getting challenged*

> megakernels are dead
cursor drops monster kitty kernel

> etched asics are dead
amd buys taalas, and etched is valued at $10b by SK Hynix and TSMC lol

whos gonna take on the remaining two theses?

*note that he was making long term calls, these are short term datapoints

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.

— https://nitter.net/waterloo_intern/status/2084426439034540297#m