Gahow Wang
4ccab0fb42
Mark KI-1 (single-sequence launch-bound, the root cause of "DDP weak scaling")
FIXED by the T10 batched forward. dim384/12L, batch 16, seq 256, 1 GPU,
back-to-back A/B:
before (single-seq): ~1653 tok/s, GPU util 0-15%, ~3 GB
after (batched): 25627 tok/s (batch16) / 40263 (batch32),
util 37% mean / 54% peak, ~10 GB
→ single-GPU ~15.5x (batch16) / ~24x (batch32); util 0-15% → 37-54%.
A single GPU at batch 32 (40K tok/s) now beats the old 4-GPU setup (3163) ~12x.
The v3 falsification history (larger batch doesn't help a single-seq design) is
kept. DDP residual weak scaling is a NEW, higher-level bottleneck batching
exposes (eager all-reduce of all params each step) → recorded as KI-5
(bucketed/overlapped all-reduce), out of T10 scope.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
xtrain
A from-scratch Rust + CUDA LLM training engine — the sibling of xserv (the inference side). GPU-first.
The goal is to learn the full training-systems stack by hand: autograd / backward passes / optimizers (AdamW) / the training loop / distributed logic. Heavy lifting is borrowed where it makes sense (GEMM → cuBLAS after a hand-written version, multi-GPU comms → NCCL, tokenizer → reused from xserv), but the core is written from scratch. The target architecture is a tiny modern transformer (RoPE + RMSNorm + SwiGLU, ~1–30M params) whose forward aligns with xserv's Qwen3, so the backward passes map one-to-one onto xserv's existing forward kernels and trained weights can flow back into xserv.
Status
Bootstrapping (P0). This repo currently contains only the project skeleton and a working Rust↔CUDA build chain, verified by a trivial vector-add CUDA kernel.
Layout
xtrain/
├── Cargo.toml # workspace
├── csrc/ # CUDA sources (.cu)
│ └── test/vecadd.cu # trivial element-wise vector-add (smoke test)
└── crates/
└── xtrain-cuda/ # CUDA Runtime FFI + build.rs (nvcc → sm_120)
├── build.rs # compiles csrc/*.cu via the `cc` crate, links cudart
├── src/ # ffi / error / device / memory
└── tests/ # vecadd smoke test
The build mirrors xserv's approach: build.rs invokes nvcc (via the cc crate)
to compile csrc/*.cu targeting sm_120 (RTX 5090) and links them into the Rust
crate over hand-written extern "C" FFI.
Building & testing
CUDA compilation and execution happen on a GPU box (dash5, 8× RTX 5090, sm_120):
export PATH=/usr/local/cuda/bin:$HOME/.cargo/bin:$PATH
cargo build
cargo test -p xtrain-cuda -- --nocapture # runs the vecadd smoke test
On a machine without nvcc/GPU, build.rs detects the missing toolchain, skips
CUDA compilation, and sets a no_cuda cfg — so host-side cargo check still
works (the GPU smoke test is compiled out).