Zachery Aaron Shores-Chmielewski
8e4987618f
Add a complete single-GPU distributed-inference example that rents a vast.ai GPU, boots a worker container, and runs a prompt end-to-end over iroh/SWIM. - examples/single-gpu-inference: add the `single_gpu_inference` orchestrator binary that starts a local iroh node, waits for the remote gpu-node to register the `"inference"` SWIM name, then sends an `InferenceRequest` and prints the response - examples/single-gpu-inference: add the `gpu_node` binary that joins the cluster via `SEED_ADDR`, spawns an `InferenceActor` over `tinygrad_worker.py`, and registers the `"inference"` bridge - inference_actor: bridge swactor messaging to a Python child process via stdin/stdout JSON, with `ProcessBridge`/`RequestBridge` adapters that satisfy the single-`Incoming` actor constraint - iroh_transport: add `IrohActorTransport` that sends `WireEnvelope`s over iroh QUIC uni-streams (connection-cached against early close), plus wire encode/decode and an inbound drain helper - vastai: add a vast.ai REST client (`find_offer` with reliability/cuda/geo filters excluding CN, `create_instance`, `wait_for_running`, `destroy_instance`) parameterised by a mockable `base_url` - worker/docs/tests: ship `tinygrad_worker.py`/`echo_worker.py` (newline-JSON, `--stub`/`--model` defaulting to llama3.2:1b), a Dockerfile, Makefile, SPEC, and actor/codec/cluster/integration/vastai test suites Signed-off-by: Zachery Aaron Shores-Chmielewski <zacheryasc@gmail.com>
27 lines
918 B
Docker
27 lines
918 B
Docker
FROM nvidia/cuda:12.6.3-devel-ubuntu24.04
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# Install Python 3, pip, and CUDA runtime compiler (tinygrad compiles kernels via NVRTC)
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RUN apt-get update && \
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apt-get install -y --no-install-recommends \
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python3 \
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python3-venv \
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python3-pip \
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ca-certificates && \
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rm -rf /var/lib/apt/lists/*
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# Install tinygrad and numpy
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RUN python3 -m pip install --no-cache-dir --break-system-packages \
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tinygrad==0.12.0 \
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numpy
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# Copy the gpu-node binary and tinygrad worker
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# Build context should be the workspace root:
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# docker build -f examples/single-gpu-inference/Dockerfile -t <tag> .
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COPY examples/single-gpu-inference/target/release/gpu-node /usr/local/bin/gpu-node
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COPY examples/single-gpu-inference/tinygrad_worker.py /usr/local/share/tinygrad_worker.py
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# Enable CUDA backend for tinygrad
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ENV CUDA=1
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ENV WORKER_SCRIPT=/usr/local/share/tinygrad_worker.py
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CMD ["gpu-node"]
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