RustBPE: High-Performance BPE Tokenizer Training in Rust
Analysis of RustBPE - a Rust implementation of BPE tokenizer training with parallel processing and performance optimizations over Python implementations.
Hello! My name is Matt Suiche. I work on AI Security at Tolmo, and I also experiment with side projects in AI Safety (Weightless, etc.) and Emulation & Operating System Research (WASM PSX, WASM NanoKrnl, etc.). I recently discussed cyberwar in the age of AI, Iran’s cyber capabilities, and how AI is reshaping hacking on Bloomberg’s Odd Lots and the National Security Lab podcast.
Previously, I founded OnDB Inc., a data infrastructure startup for the agentic economy, and co-founded CloudVolumes (acquired by VMware in 2014) and Comae Technologies (acquired by Magnet Forensics in 2022), where I later served as Head of Detection Engineering. I also founded the cybersecurity community project OPCDE.
My path into technology started in reverse engineering as a teenager, and has since spanned memory forensics, operating systems, virtualization, blockchain, and now AI infrastructure.
Analysis of RustBPE - a Rust implementation of BPE tokenizer training with parallel processing and performance optimizations over Python implementations.
Learning GPU performance engineering through the GPU MODE TriMul challenge - achieving 2.42× speedup on H100 through FP16 optimization, weight fusion, and systematic experimentation.
GPU production constraints are creating infrastructure bottlenecks. Multi-GPU programming, particularly vendor-agnostic implementations, has become essential. In their GPU Mode presentation, AMD Research engineers Muhammad Awad, Muhammad …