Rust tool that mmaps previous checkpoint, diffs against live GPU weights
(via CUDA IPC handles), and only writes changed blocks. For small
behavioral training steps, turns 54GB write into ~500MB.
Also includes vllm_export_hook.py with direct source patch approach —
exports IPC handles from vLLM's worker subprocess after model load.
Run every 10 minutes via cron to protect against vLLM crashes.
Daily rsync to moria for long-term storage.
Core components for online fine-tuning of Qwen3.5-27B with CUDA IPC
shared weight memory between vLLM and the training process:
- apollo_mini.py: rank-1 optimizer (SGD memory, AdamW quality)
- apollo_worker.py: HTTP daemon coordinating training with vLLM
- weight_mapping.py: vLLM merged → HF separate layout (zero-copy views)
- training_example.py: tokenization with chat template
- export_weights.py: CUDA IPC handle export from vLLM
- train.py: standalone training script (alternative to daemon)
- DESIGN.md: architecture and protocol documentation
Validated: CUDA IPC autograd works on real Qwen3.5 weights (B200).
Apollo-Mini rank-1 projection + scaling + in-place update confirmed.
Co-Authored-By: Kent Overstreet <kent.overstreet@gmail.com>
