Workflows vs Agents for Code Translation
Compares structured workflows versus agentic approaches for MATLAB-to-HDL translation, showing that agentic methods with the Model Context Protocol increase simulation reach rates by over 20 percentage points on mid-sized models.
Abstract
This paper compares two LLM-driven approaches for syntax repair in MATLAB-to-HDL translation. The researchers evaluated a structured, expert-designed flow versus an agentic method using the Model Context Protocol across three model sizes (Qwen 8B/30B/235B) on 42 signal-processing functions. The agentic approach achieved superior results on mid-sized models, increasing the simulation reach rate by over 20 percentage points on the 30B model. The authors attribute gains to short prompts, aggressive context management, and conditional tool use, noting that agent-based frameworks are most effective at compensating for the capacity limits of small and mid-sized models.
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