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cs.LG2025
Iceberg: Enhancing HLS Modeling with Synthetic Data
Zijian Ding, Tung Nguyen, Weikai Li +3
Deep learning-based prediction models for High-Level Synthesis (HLS) of hardware designs often struggle to generalize. In this paper, we study how to close the generalizability gap…
cs.AR2025★ 1 cited
LLM-DSE: Searching Accelerator Parameters with LLM Agents
Hanyu Wang, Xinrui Wu, Zijian Ding +6
Even though high-level synthesis (HLS) tools mitigate the challenges of programming domain-specific accelerators (DSAs) by raising the abstraction level, optimizing hardware direct…
cs.LG2025
LIFT: LLM-Based Pragma Insertion for HLS via GNN Supervised Fine-Tuning
Neha Prakriya, Zijian Ding, Yizhou Sun +1
FPGAs are increasingly adopted in datacenter environments for their reconfigurability and energy efficiency. High-Level Synthesis (HLS) tools have eased FPGA programming by raising…