← Back

Learning Rust for High-Performance Inference

Writing

Python is the lingua franca of ML, but inference serving is a systems problem. Rust gives you the performance of C++ with memory safety guarantees.

Learning Path

  1. Rust fundamentals — ownership, borrowing, lifetimes
  2. Async with Tokio — building concurrent HTTP/gRPC servers
  3. ONNX Runtime Rust bindings — running models without Python overhead
  4. Zero-copy tensor handling — minimizing allocations in the hot path

Goal

Build a lightweight inference server that can serve ONNX models with sub-millisecond overhead, suitable for real-time applications where Python’s GIL is the bottleneck.