59 citations · 97 across the 9 of their papers we have counts for
4 papers · 1 filter
LLMulator: Generalizable Cost Modeling for Dataflow Accelerators with Input-Adaptive Control Flow
Kaiyan Chang, Wenlong Zhu, Shengwen Liang +2
Accurate and fast performance prediction for dataflow-based accelerators is vital for efficient hardware design and design space exploration, yet existing methods struggle to gener…
Graphitron: A Domain Specific Language for FPGA-based Graph Processing Accelerator Generation
Xinmiao Zhang, Zheng Feng, Shengwen Liang +4
FPGA-based graph processing accelerators, enabling extensive customization, have demonstrated significant energy efficiency over general computing engines like CPUs and GPUs. Nonet…
Natural language is not enough: Benchmarking multi-modal generative AI for Verilog generation
Kaiyan Chang, Zhirong Chen, Yunhao Zhou +9
Natural language interfaces have exhibited considerable potential in the automation of Verilog generation derived from high-level specifications through the utilization of large la…
Data is all you need: Finetuning LLMs for Chip Design via an Automated design-data augmentation framework
Kaiyan Chang, Kun Wang, Nan Yang +16
Recent advances in large language models have demonstrated their potential for automated generation of hardware description language (HDL) code from high-level prompts. Researchers…