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309b968 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | # DaisyChain demo cluster: 3 node containers + a dashboard on one Docker network.
# In production each node is a real machine (see docs/TAILSCALE.md); this brings
# the whole thing up on one box so you can see it work.
#
# docker compose -f docker/docker-compose.yml up --build
# open http://localhost:8080
name: daisychain
x-node: &node
build: { context: .., dockerfile: docker/Dockerfile }
image: daisychain:latest
environment: &env
MASTER_ADDR: rank0
MASTER_PORT: "29560"
WORLD_SIZE: "3"
DAISY_STEPS: "300"
DAISY_STEP_SLEEP: "0.1" # demo pacing so the dashboard shows it live
# train through the emulated GPU logic (verified INT8 units) by default
DAISY_TASK: "daisychain.verified_task:VerifiedTask"
networks: [cluster]
services:
rank0:
<<: *node
environment: { <<: *env, RANK: "0", DAISY_CAPACITY: "8000" }
rank1:
<<: *node
depends_on: [rank0]
environment: { <<: *env, RANK: "1", DAISY_CAPACITY: "4000" }
rank2:
<<: *node
depends_on: [rank0]
environment: { <<: *env, RANK: "2", DAISY_CAPACITY: "2000" }
dashboard:
build: { context: .., dockerfile: docker/dashboard.Dockerfile }
image: daisychain-dashboard:latest
depends_on: [rank0, rank1, rank2]
environment:
DAISY_NODES_FILE: config/nodes.example.json
DAISY_EXPECTED_WORLD: "3"
DAISY_BASE_BATCH: "32"
ports: ["8080:8080"]
networks: [cluster]
networks:
cluster: { driver: bridge }
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