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cortex/crates/neuron/Cargo.toml
rob thijssen da068ded6d
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Stage 7a-ii: real NCCL handshake behind the worker pool
Wires cudarc::nccl into the TP worker lifecycle introduced in 7a-i.
With --features cuda the leader and its workers now establish a live
NCCL communicator end-to-end; without the feature the same code paths
return Error{kind="cuda_feature_not_enabled"} so a misconfigured
build is obvious instead of silently no-op.

NCCL state machine (harness/tp/nccl_state.rs) is shared between the
worker process and the leader's pool:
- generate_comm_id_hex() mints an Id::new() on the leader.
- NcclState::init parses 256 hex chars → [c_char; 128] → Id::uninit,
  opens a CudaContext on the configured device, calls Comm::from_rank
  with the supplied (rank, world_size, id). NCCL blocks until every
  rank has joined.
- NcclState::sanity_check runs one all_reduce(1u32, Sum); the leader
  asserts every rank reports observed_sum == world_size.
- NCCL handles serialised under Mutex; unsafe impl Send/Sync gates
  the Comm across spawn_blocking boundaries (NCCL is move-safe; only
  concurrent op issuance is unsafe).

WorkerPool::init_nccl orchestrates the rendezvous:
1. Write Init { comm_id } to every worker's stdin (no await yet).
2. Leader rank 0 calls its own Comm::from_rank in spawn_blocking,
   concurrently with workers.
3. NCCL handshake completes for all ranks simultaneously.
4. Leader collects InitOk responses.
WorkerPool::nccl_sanity_check follows the same pattern over
all_reduce, validating world_size == observed_sum on every rank.

Worker.send_only / Worker.recv_only split out from the previous
monolithic Worker.request so the leader can interleave its own NCCL
work with the worker calls — required because NCCL blocks during
init.

Tests:
- 4 hex roundtrip unit tests for the wire encoding.
- The 7a-i "not implemented" expectation now reads
  "cuda_feature_not_enabled" on the local dev box (no CUDA), or
  accepts InitOk on a cuda-built test binary.
- New cuda-integration test in tp_worker_lifecycle_cuda.rs covers
  the real init + sanity round-trip; gated on the cuda-integration
  feature so default CI doesn't try to NCCL.

Verifiable on beast (2× RTX 5090):
  cargo test -p neuron --features cuda-integration \
        --test tp_worker_lifecycle_cuda

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-19 16:40:01 +03:00

77 lines
2.2 KiB
TOML

[package]
name = "neuron"
version.workspace = true
edition.workspace = true
license.workspace = true
[lib]
name = "neuron"
path = "src/lib.rs"
[[bin]]
name = "neuron"
path = "src/main.rs"
[features]
default = []
# Enables CUDA acceleration in candle and the cudarc/nccl bindings the
# TP worker pool uses. Without this feature, candle compiles for CPU
# only, Device::new_cuda calls fall back to CPU, and TP Init/sanity
# requests return Error{kind="cuda_feature_not_enabled"}.
cuda = [
"candle-core/cuda",
"candle-core/nccl",
"candle-nn/cuda",
"candle-transformers/cuda",
"dep:cudarc",
]
# Use cuDNN for convolution / attention kernels. Requires CUDA.
cudnn = [
"cuda",
"candle-core/cudnn",
"candle-nn/cudnn",
"candle-transformers/cudnn",
]
# FlashAttention kernels. Requires CUDA.
flash-attn = [
"cuda",
"candle-transformers/flash-attn",
]
# Reserved for GPU-only integration tests in later stages.
cuda-integration = ["cuda"]
[dependencies]
cortex-core.workspace = true
tokio.workspace = true
axum.workspace = true
serde.workspace = true
serde_json.workspace = true
reqwest.workspace = true
tracing.workspace = true
tracing-subscriber.workspace = true
anyhow.workspace = true
async-trait.workspace = true
clap.workspace = true
thiserror.workspace = true
futures.workspace = true
tokio-stream.workspace = true
figment.workspace = true
toml.workspace = true
# candle for in-process inference. CUDA support is gated behind the
# crate's `cuda` feature (default off) so the workspace builds on
# non-CUDA hosts and CI runners.
candle-core = "0.10.2"
candle-nn = "0.10.2"
candle-transformers = "0.10.2"
# Direct dep on cudarc (matching candle's transitive version) so the
# TP worker pool can call cudarc::nccl::{Comm, Id} directly. Gated on
# the `cuda` feature; same toolchain requirement as candle's CUDA path.
cudarc = { version = "0.19", optional = true, default-features = false, features = ["nccl", "cuda-version-from-build-system"] }
tokenizers = { version = "0.22", default-features = false, features = ["onig"] }
hf-hub = { version = "0.4", features = ["tokio"] }
[dev-dependencies]
tokio = { workspace = true, features = ["test-util"] }
reqwest.workspace = true