[beta] Decentralized sharded WebGPU compute pool

[ThyFriendlyFox]

Summary

A beta scaffold for a decentralized, sharded WebGPU compute pool: many browser GPUs cooperating to run inference-style workloads, contributed voluntarily to form a shared pool. Off by default behind a feature flag and fully isolated from the existing app.

How it works

Large-model inference is dominated by big matrix multiplies (the core transformer-layer op). The pool splits each matmul into row-block shards and spreads them across every participating GPU, then reassembles the result. Each node is both a worker (computes shards for others) and a requester (dispatches its own jobs).

coordinator (signaling/membership only — never sees shard data)
        ▲                          ▲
   join/SDP/ICE                join/SDP/ICE
   Node A  ◀──── shards over WebRTC datachannel ────▶  Node B
   ComputePool: webgpu · ShardScheduler · PeerLink

What's included (src/compute/)

File	Role
webgpu.ts	Real WGSL matmul kernel, GPU capability probe, benchmark
ShardScheduler.ts	Pure split / build / merge + weighted work-stealing
signaling.ts	WebSocket client to the coordinator
peer.ts	PeerLink — a peer as a remote Worker over RTCDataChannel
ComputePool.ts	Orchestrates GPU + peers; runSharded() / runDemo()
ComputePoolView.ts	Beta control panel (status, demo run, per-shard log)
types.ts	Task/result/signaling/peer protocol types

Plus compute-coordinator/ — a tiny reference signaling/membership broker (relays WebRTC handshakes only; shard payloads go peer-to-peer).

Enabling

VITE_ENABLE_COMPUTE_POOL=true
VITE_COMPUTE_COORDINATOR_URL=ws://localhost:8787   # optional; omit for solo
VITE_COMPUTE_POOL_ID=mouse-public-beta

A ⚡ launcher then opens the panel. With no coordinator the pool runs as a single node ("solo") and still demonstrates the full shard → compute → merge pipeline on one GPU.

Testing

• npm run build (tsc + vite) passes; the compute module is isolated and the app is unchanged when the flag is off.
• Verified the reference coordinator end-to-end over WebSockets: join, peer list, peer_joined, signal relay, and peer_left all pass.
• The WebGPU kernel and peer datachannel paths require a real browser GPU / ≥2 nodes to exercise live; the solo shard pipeline is the tested-by-construction path.

Beta limitations (see src/compute/README.md)

• Job primitive is a dense f32 matmul; mapping real model weights/layers on top is future work.
• Non-tiled kernel (correct, not yet throughput-tuned).
• No peer result verification/reputation, weight encryption, or anti-abuse — all required before any real public "free inference" deployment.

Note: native iOS sim build (npm run cap:ios:sim) not run here (no Xcode on this Linux VM). WebGPU/WebRTC availability also varies by platform/WebView.