🚀 [tutorial]Update: Reverse-Engineering Breakdown Released — “The Muon is Scalable” (CPU-Friendly) Blueprint

Show and Tell
1

Following the momentum from my original Understanding the Muon Optimizer tutorial (which crossed 1300+ downloads in first two months), I’ve just released a new distributed edition:
:backhand_index_pointing_right: bird-of-paradise/muon_distributed

This version dives deeper into the system engineering side of Moonshot AI’s “Muon is Scalable for LLM Training” paper — showing how the distributed “acrobatics” of ZeRO-1 (DP) and Tensor Parallelism (TP) come together in practice.

Key highlights:

  • CPU-friendly (uses gloo, so anyone can run it)

  • Annotated end-to-end distributed flow (DP gather → TP gather → Newton–Schulz → TP shard → DP shard)

  • Cleaned logic for buffer_idx vs bucket_idx

  • Fixed multiple bugs from the Moonshot PoC version (see README table)

This code is the practical companion to my Medium series “The Turtle Speed Breakthrough :turtle::sparkles:” — where I documented every aha-moment of reverse-engineering this work:

:brain: Next step: testing and optimizing coalesced all_gather for scalability (8+ GPUs).
If anyone has compute or wants to join the chaos, come hang out in our Discord study group.

Let’s make distributed training less mysterious — one stubborn potato :potato: step at a time.

1 Like