Porting CUDA FFT to Mojo: Achieving Bit-Exact Precision
Porting a CUDA Fast Fourier Transform implementation to Mojo required deep PTX assembly analysis and understanding floating-point nondeterminism to achieve bit-exact precision matching
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.
Porting a CUDA Fast Fourier Transform implementation to Mojo required deep PTX assembly analysis and understanding floating-point nondeterminism to achieve bit-exact precision matching
Technical analysis of AMD GPU support implementation in Triton's Gluon framework, including architecture-specific optimizations and performance characteristics.
Analysis of RustBPE - a Rust implementation of BPE tokenizer training with parallel processing and performance optimizations over Python implementations.