peercache 0.1.1

Peer-to-peer RDMA zero-copy L3 KV-cache backend for SGLang HiCache

PeerCache

A lightweight, peer-to-peer L3 storage backend for SGLang HiCache.

Docs: https://flymysql.github.io/PeerCache/

PeerCache gives you Mooncake-style RDMA zero-copy KV-cache sharing across nodes, but without the centralized master + metadata services. Instead it uses:

• Embedded service discovery — no separate meta process. One node (chosen by discovery_addr) auto-hosts the discovery service in-process; nodes register their endpoint, heartbeat, and pull the live membership list.
• A consistent-hash distributed directory (DHT) — the mapping key -> {data_node, remote_addr, rkey, length} is sharded across all nodes by hashing the key. There is no central metadata store.
• Data stays local on write — set() copies the page into a node-local published pool (a host memcpy, no network, no master) and pushes only a tiny location record to the directory.
• One-sided RDMA READ on read — get() looks up the directory, then issues a zero-copy IBV_WR_RDMA_READ straight into SGLang's registered host buffer.

write:  set() ── local memcpy ──> published pool MR
                └── PUT key->{node,addr,rkey,len} ──> directory shard (hash(key))
read:   get() ── GET key ──> directory shard ──> {node,addr,rkey,len}
                └── one-sided RDMA READ ──> local host buffer (zero copy)

Why simpler than Mooncake?

	Mooncake	PeerCache
metadata	central master + metadata service	sharded directory (consistent hash)
data placement	dedicated managed pool	stays on producing node
coordination	master allocates / tracks objects	only service discovery on meta node
transfer	RDMA zero-copy	RDMA zero-copy (one-sided READ)

Architecture

• C++ data plane (cpp/): raw libibverbs + librdmacm. RC QPs, one-sided READ/WRITE, CQ polling, lazy per-peer connection pooling. Exposed to Python via pybind11 as the _peercache module.
• Python control plane (python/peercache/): TCP RPC, service discovery, consistent-hash ring, distributed directory, and the published-pool with LRU.
• TCP fallback transport: a pure-Python transport that mirrors the RDMA API so the design can be validated end-to-end on machines without RDMA hardware.

Two-MR model (correctness)

SGLang's host KV buffer is the L2 tier and is evicted/overwritten by HiCache, so we cannot register its address into the directory directly (dangling reference). Each node therefore registers two memory regions:

1. Receive MR = mem_pool_host.kv_buffer — destination of one-sided READ on get.
2. Published pool MR = a backend-owned host pool with LRU — source of READ on remote nodes. set memcpys the page into this pool (node-local, no network) and publishes its addr+rkey+len to the directory. Eviction from the pool deletes the corresponding directory entry, so a published address stays valid until evicted.

Install

# Linux with RDMA (Mellanox OFED / rdma-core dev headers installed)
pip install .

# Without RDMA (control-plane + TCP fallback only, e.g. for tests on a laptop)
pip install -e . --config-settings=cmake.define.PEERCACHE_NO_RDMA=ON

Run with SGLang

The meta service is embedded — there is no separate meta process. Point discovery_addr at one node's IP on every node; the node whose IP matches auto-starts the discovery service in-process.

# On every SGLang node, set discovery_addr to the SAME node's IP (say node-0).
# node-0 detects the IP is itself and hosts the embedded meta automatically.
python -m sglang.launch_server --enable-hierarchical-cache \
  --hicache-storage-backend dynamic \
  --hicache-storage-backend-extra-config \
  '{"backend_name":"peercache","module_path":"peercache.store","class_name":"PeerCacheStore","discovery_addr":"NODE0_IP:9100","protocol":"rdma","device_name":"mlx5_0","global_segment_size":"4gb"}'

(Optionally, you can still run a standalone meta with peercache-meta --bind 0.0.0.0:9100 if you prefer a dedicated discovery host.)

See examples/sglang_launch.md for details.

Test

pip install pytest
PYTHONPATH=python pytest tests/ -v

Maintainer setup (one-time)

• GitHub Pages: Settings → Pages → Build and deployment → Source = GitHub Actions. The Docs workflow then publishes to https://flymysql.github.io/PeerCache/ on every push to main.
• PyPI Trusted Publishing: on the PyPI peercache project, add a GitHub publisher (owner flymysql, repo PeerCache, workflow release.yml, environment pypi). Tagging vX.Y.Z then builds the sdist, attaches it to a GitHub Release, and publishes to PyPI. Until configured, the PyPI step is non-blocking and the GitHub Release still ships the package.