# From Pragmas to Partners: A Symbiotic Evolution of Agentic High-Level Synthesis

arXiv: https://arxiv.org/abs/2602.01401 · HTML: https://mlsanity.com/paper/2602.01401/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use.
- Builds on 16 of its 40 references that are in the map.
- First posted on arXiv 1 Feb 2026.

## Placed in

- LLM agents and tool use / [Software engineering coding agents](https://mlsanity.com/agents/software-engineering-coding-agents/)

## Builds on (most cited first, 16 of 16)

- [Chip-Chat: Challenges and Opportunities in Conversational Hardware Design](https://mlsanity.com/paper/2305.13243/) (2023)
- [Automated C/C++ Program Repair for High-Level Synthesis via Large Language Models](https://mlsanity.com/paper/2407.03889/) (2024)
- [Allo: A Programming Model for Composable Accelerator Design](https://mlsanity.com/paper/2404.04815/) (2024)
- [C2HLSC: Leveraging Large Language Models to Bridge the Software-to-Hardware Design Gap](https://mlsanity.com/paper/2412.00214/) (2024)
- [HLS-Eval: A Benchmark and Framework for Evaluating LLMs on High-Level Synthesis Design Tasks](https://mlsanity.com/paper/2504.12268/) (2025)
- [LLM-DSE: Searching Accelerator Parameters with LLM Agents](https://mlsanity.com/paper/2505.12188/) (2025)
- [Can Reasoning Models Reason about Hardware? An Agentic HLS Perspective](https://mlsanity.com/paper/2503.12721/) (2025)
- [SAGE-HLS: Syntax-Aware AST-Guided LLM for High-Level Synthesis Code Generation](https://mlsanity.com/paper/2508.03558/) (2025)
- [ChatHLS: Towards Systematic Design Automation and Optimization for High-Level Synthesis](https://mlsanity.com/paper/2507.00642/) (2025)
- [TimelyHLS: LLM-Based Timing-Aware and Architecture-Specific FPGA HLS Optimization](https://mlsanity.com/paper/2507.17962/) (2025)
- [Predictable Accelerator Design with Time-Sensitive Affine Types](https://mlsanity.com/paper/2004.04852/) (2020)
- [LiteX: an open-source SoC builder and library based on Migen Python DSL](https://mlsanity.com/paper/2005.02506/) (2020)
- [LightningSimV2: Faster and Scalable Simulation for High-Level Synthesis via Graph Compilation and Optimization](https://mlsanity.com/paper/2404.09471/) (2024)
- [SystolicAttention: Fusing FlashAttention within a Single Systolic Array](https://mlsanity.com/paper/2507.11331/) (2025)
- [Modular Hardware Design with Timeline Types](https://mlsanity.com/paper/2304.10646/) (2023)
- [OmniSim: Simulating Hardware with C Speed and RTL Accuracy for High-Level Synthesis Designs](https://mlsanity.com/paper/2508.19299/) (2025)

## Abstract (arXiv)

The rise of large language models has sparked interest in AI-driven hardware design, raising the question: does high-level synthesis (HLS) still matter in the agentic era? We argue that HLS remains essential. While we expect mature agentic hardware systems to leverage both HLS and RTL, this paper focuses on HLS and its role in enabling agentic optimization. HLS offers faster iteration cycles, portability, and design permutability that make it a natural layer for agentic optimization. This position paper makes three contributions. First, we explain why HLS serves as a practical abstraction layer and a golden reference for agentic hardware design. Second, we identify key limitations of current HLS tools, namely inadequate performance feedback, rigid interfaces, and limited debuggability that agents are uniquely positioned to address. Third, we propose a taxonomy for the symbiotic evolution of agentic HLS, clarifying how responsibility shifts from human designers to AI agents as systems advance from copilots to autonomous design partners.