6 citations · 10 across the 4 of their papers we have counts for
4 papers · 1 filter
Benchmarking Agentic HLS Design Tasks With HLS-Eval
Stefan Abi-Karam, Callie Hao
Large language models (LLMs) and AI agents are increasingly explored for hardware design, including high-level digital design. While most work targets code generation and editing f…
HLSFactory-Agent: Large-Scale Agentic HLS Dataset Construction from Academic and Open-Source Projects
Kaushik Chandana, Jay Imperatori, Tanmay Shukla +3
Building large, diverse datasets of high-level synthesis (HLS) designs beyond common community benchmarks remains an open challenge. This challenge is made urgent by the rise of de…
HLS-Eval: A Benchmark and Framework for Evaluating LLMs on High-Level Synthesis Design Tasks
Stefan Abi-Karam, Cong Hao
The rapid scaling of large language model (LLM) training and inference has driven their adoption in semiconductor design across academia and industry. While most prior work evaluat…
HLSFactory: A Framework Empowering High-Level Synthesis Datasets for Machine Learning and Beyond
Stefan Abi-Karam, Rishov Sarkar, Allison Seigler +7
Machine learning (ML) techniques have been applied to high-level synthesis (HLS) flows for quality-of-result (QoR) prediction and design space exploration (DSE). Nevertheless, the…