From Pragmas to Partners: A Symbiotic Evolution of Agentic High-Level Synthesis
On the map: LLM agents and tool use → Software engineering coding agents
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.
Key facts. No citing papers in the map yet (data through 7 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.
Builds on
16 of 40 references.
Closest ancestors · 2
Same direction, newest first
- 2025LLM-DSE: Searching Accelerator Parameters with LLM Agents18 May
- 2025Can Reasoning Models Reason about Hardware? An Agentic HLS Perspective17 Mar
Other references · 14
- 2023Chip-Chat: Challenges and Opportunities in Conversational Hardware Designcited by 136
- 2024Automated C/C++ Program Repair for High-Level Synthesis via Large Language Modelscited by 18
- 2024Allo: A Programming Model for Composable Accelerator Designcited by 16
- 2024C2HLSC: Leveraging Large Language Models to Bridge the Software-to-Hardware Design Gapcited by 16
- 2025HLS-Eval: A Benchmark and Framework for Evaluating LLMs on High-Level Synthesis Design Taskscited by 10
- 2025SAGE-HLS: Syntax-Aware AST-Guided LLM for High-Level Synthesis Code Generationcited by 9
- 2025ChatHLS: Towards Systematic Design Automation and Optimization for High-Level Synthesiscited by 6
- 2025TimelyHLS: LLM-Based Timing-Aware and Architecture-Specific FPGA HLS Optimizationcited by 5
- 2020Predictable Accelerator Design with Time-Sensitive Affine Typescited by 4
- 2020LiteX: an open-source SoC builder and library based on Migen Python DSLcited by 4
- 2024LightningSimV2: Faster and Scalable Simulation for High-Level Synthesis via Graph Compilation and Optimizationcited by 3
- 2023Modular Hardware Design with Timeline Typescited by 2
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- 2026Can Agents Design Better Chips with a Higher Level Abstraction?
- 2026Agentic Architect: An Agentic AI Framework for Architecture Design Exploration and Optimization
- 2024SynthAI: A Multi Agent Generative AI Framework for Automated Modular HLS Design Generation
- 2026Agent Factories for High Level Synthesis: How Far Can General-Purpose Coding Agents Go in Hardware Optimization?
- 2024Agentic-HLS: An agentic reasoning based high-level synthesis system using large language models (AI for EDA workshop 2024)
- 2026Agentic Hardware Design as Repository-Level Code Evolution
- 2026ContractHIL-HLS: Contract-Aligned Multi-Agent Workflow with Hardware-in-the-Loop Feedback for HLS Design
- 2025Control Plane as a Tool: A Scalable Design Pattern for Agentic AI Systems