C2HLSC: Can LLMs Bridge the Software-to-Hardware Design Gap?
Abstract
High Level Synthesis (HLS) tools offer rapid hardware design from C code, but their compatibility is limited by code constructs. This paper investigates Large Language Models (LLMs) for refactoring C code into HLS-compatible formats. We present several case studies by using an LLM to rewrite C code for NIST 800-22 randomness tests, a QuickSort algorithm and AES-128 into HLS-synthesizable c. The LLM iteratively transforms the C code guided by user prompts, implementing functions like streaming data and hardware-specific signals. This evaluation demonstrates the LLM's potential to assist hardware design refactoring regular C code into HLS synthesizable C code.
Turn this paper into a full lesson
ArcXiv compiles a staged curriculum from this paper: 8-12 lessons across beginner → advanced, synthesised section guides, visuals, flashcards, a quiz, exercises, and on-demand deep dives per section. Grounded in the abstract, never invented.