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Quick start
The main branch contains runnable Rust code for G3.5 shared KV caching over CPU/TCP. Start with the software contract tests; no GPU or DPU is required.
Source code is available. There is no installable release or production deployment qualification.
Build and test from source
Use stable Rust with Cargo, Git, and Python 3. Fetch dependencies on the first run. Test payloads are synthetic KV blocks, not output from an inference model.
git clone https://github.com/rustfs/GPUCache.git
cd GPUCache
cargo test --workspace --all-targetsRun the CPU demos
Run these demos without GPUCACHE_RUSTFS_* endpoint or credential settings. The cold demo uses the default mock; it is not a live RustFS validation.
cargo run -p gpucache-transport --bin share-demo
cargo run -p gpucache-transport --bin shard-demo
cargo run -p gpucache-cold --bin cold-demo
cargo run -p gpucache-storage --bin engine-spike
cargo run -p gpucache-dpu --bin dpu-demoThe expected labels are REUSE_OK, SHARD_OK, COLD_CONTRACT_OK, FAKE_BLOCK_CONTRACT_OK and DPU_CONTRACT_OK. The engine spike checks fake whole blocks. The DPU demo is a host simulation. Neither label means a real engine or device ran.
Reproduce the full CPU regression
The runner checks formatting, dependencies, Clippy, tests, optional features and demos. It disables live RustFS access and saves summary.md, results.json, JUnit and logs. Use a new output directory for each run; --offline requires dependencies to have been fetched.
cargo fetch --locked
python3 scripts/ci/vm_regression.py --profile cpu --offline --output artifacts/cpu-docsWhat this does not qualify
Real vLLM export/import, RDMA, GDS and BlueField-3 remain NOT_RUN_HARDWARE; the GPU/model campaign is NOT_RUN_BUDGET. No active zero-copy path, hardware performance result or hot-tier durability replica is implied.
Related documentation
Architecture · Roadmap · Scaling and deployment boundaries · CPU_COMPLETION.md