Skip to main content

memkv-lmcache

LMCache StoragePluginInterface backend that persists KV chunks in a remote MemKV cluster. Loaded as a vendor plugin via LMCache's storage_plugins dynamic loader — no patches to LMCache's tree.

vLLM gets a MemKV-backed prefix KV-state path for free through vllm/distributed/kv_transfer/kv_connector/v1/lmcache_connector.py — no separate vLLM connector package is required.

Build

cd lmcache-plugin
pip install maturin
maturin develop --release      # local dev install
# or
maturin build --release        # wheel under target/wheels/
pip install target/wheels/memkv_lmcache-*.whl

The wheel bundles a native PyO3 extension built from the same memkv-client crate the NIXL plugin and the sglang plugin use, so RDMA/TCP transport selection works the same way across all three.

Configure the MemKV connection

The plugin reads the standard MemKV config chain — MEMKV_CONFIG yaml first, then MEMKV_* env vars:

export MEMKV_SERVERS="10.0.0.10:9900,10.0.0.11:9900"
export MEMKV_RDMA_DEVICES="mlx5_0,mlx5_1"
export MEMKV_AUTH_KEY="<64-hex>"
# optional:
# export MEMKV_TRANSPORT=auto
# export MEMKV_CONFIG=/etc/memkv.yaml

Configure LMCache

Add the plugin to your LMCache yaml. max_local_cpu_size must be > 0 because the plugin uses LocalCPUBackend's allocator to stage retrieved tensors:

chunk_size: 64
local_cpu: true
max_local_cpu_size: 5
storage_plugins: memkv
extra_config:
  storage_plugin.memkv.module_path: memkv_lmcache.backend
  storage_plugin.memkv.class_name: MemKVStorageBackend

Launch vLLM with LMCache + MemKV

LMCACHE_CONFIG_FILE=/etc/lmcache.yaml \
KV_TRANSFER_CONFIG='{"kv_connector":"LMCacheConnectorV1","kv_role":"kv_both"}' \
vllm serve meta-llama/Llama-3-8B \
    --tensor-parallel-size 1 \
    --kv-transfer-config "$KV_TRANSFER_CONFIG"

LMCache's connector picks the storage_plugins entry up at startup and routes prefix KV reads/writes through MemKVStorageBackend.

What's implemented

Method Status
contains yes (in-process _meta check — a key only counts as present when its shape/dtype metadata is on file, so a fresh process reports miss for server-resident bytes it cannot reconstruct); batched_contains falls through to StoragePluginInterface's default loop
exists_in_put_tasks yes (in-process tracking set)
batched_submit_put_task yes (synchronous; returns None)
get_blocking yes (requires prior put in this process — see Caveats)
remove yes
pin / unpin yes (presence-check only — wire layer has no per-client retention)
get_allocator_backend yes (delegates to LocalCPUBackend)
close yes

Caveats

  • Cross-restart warm cache is MVP-restricted. Each engine process keeps shape/dtype/fmt in an in-memory dict so get_blocking knows what MemoryObj to allocate. The wire bytes survive in MemKV across restarts; the local metadata does not. A fresh process therefore starts cold even when MemKV holds the chunks. This matches LMCache's LocalDiskBackend behavior. Encoding the shape header on the wire is a follow-up.
  • Key length cap. MemKV's protocol caps keys at 512 bytes; CacheEngineKey.to_string() shapes longer than 480 bytes collapse to a memkv-h2:<blake2b-256> digest.
  • Pin/unpin are local-only. MemKV has no per-client retention policy, so the methods are presence checks against the local meta dict. Server-side eviction is owned by the MemKV cluster.
  • Reads ride the server-driven chunked BatchRead. get_blocking uses batch_get_into, which streams the full value through the server's bounce buffers into per-thread staging with strict full-length-or-miss semantics. The single-key zero-copy get_into (client-driven RDMA READ) remains available but is not the LMCache default: under sustained burst load it saturated the per-connection RC send CQ tail and tripped vLLM's SPMD broadcast timeout, and it faults the value resident server-side.

Layout

lmcache-plugin/
├── Cargo.toml                      # cdylib + pyo3 + memkv-client
├── pyproject.toml                  # maturin
├── src/lib.rs                      # PyO3 wrapper around memkv-client::Engine
└── python/memkv_lmcache/
    ├── __init__.py                 # re-exports Client
    └── backend.py                  # MemKVStorageBackend(StoragePluginInterface)

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

memkv_lmcache-1.0.2-cp38-abi3-manylinux_2_28_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.8+manylinux: glibc 2.28+ x86-64

memkv_lmcache-1.0.2-cp38-abi3-manylinux_2_28_aarch64.whl (1.4 MB view details)

Uploaded CPython 3.8+manylinux: glibc 2.28+ ARM64

File details

Details for the file memkv_lmcache-1.0.2-cp38-abi3-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for memkv_lmcache-1.0.2-cp38-abi3-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 e491b42237079d54440b820e45ae61fcfdf240989dcc9a581de64cf30f52d173
MD5 ccc1923c46e93fa9c33de0511155308d
BLAKE2b-256 0eaa1e22987642be06a5f35d38e269ba9a12067ff81f90df5bbd1d77b398b6db

See more details on using hashes here.

File details

Details for the file memkv_lmcache-1.0.2-cp38-abi3-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for memkv_lmcache-1.0.2-cp38-abi3-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 1bdc683cddf5024760192901c5502761267912465926e97be80ed882d6fb8708
MD5 2f6d0dc0cd57d3d3f0af45292be04343
BLAKE2b-256 30cbbda1e11f025b4aa8a29ed3e82ddefaac22f103227fbccc125e4f0c024c0d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page