Algorithms + Data Structures = Programs Episode 240: Thrust, Rust vs C++, Python & More (Part 2)
10 snips
Jun 27, 2025 Jared Hoberock, a key figure at NVIDIA Research and co-creator of the Thrust parallel algorithms library, dives into the quirks of programming languages in this engaging discussion. He shares humorous insights on Thrust's naming conventions and the iconic T-shirt linked to the project. The conversation shifts to the future of parallel programming and how asynchrony could reshape GPU programming. Jared also debates the pros and cons of Python versus C++ and Rust for GPU tasks, exploring Python's evolving role in high-performance computing.
AI Snips
Chapters
Books
Transcript
Episode notes
Thrust's Controversial Naming Anecdote
- The original name for the Thrust library was the communist-themed "comrade" with a K.
- This name was quickly changed after criticism from an influential NVIDIA figure.
Ideal GPU Language Features
- An ideal language for GPU parallelism must handle asynchrony, heterogeneity, and be tensor-based rather than sequence-based.
- These features would better match GPU hardware and enable superior parallel algorithm libraries.
Rust's Limitations for GPU Parallelism
- Rust is great for single-threaded code but struggles with GPU parallelism due to its borrow checker model.
- The borrow checker assumes sequential calls, conflicting with GPU thread communication and mutation needs.
