10 papers · 1 filter
VeriInteresting: An Empirical Study of Model Prompt Interactions in Verilog Code Generation
Luca Collini, Andrew Hennesee, Patrick Yubeaton +2
Rapid advances in language models (LMs) have created new opportunities for automated code generation while complicating trade-offs between model characteristics and prompt design c…
Need for zkSpeed: Accelerating HyperPlonk for Zero-Knowledge Proofs
Alhad Daftardar, Jianqiao Mo, Joey Ah-kiow +4
Zero-Knowledge Proofs (ZKPs) are rapidly gaining importance in privacy-preserving and verifiable computing. ZKPs enable a proving party to prove the truth of a statement to a verif…
LLM-Aided Testbench Generation and Bug Detection for Finite-State Machines
Jitendra Bhandari, Johann Knechtel, Ramesh Narayanaswamy +2
This work investigates the potential of tailoring Large Language Models (LLMs), specifically GPT3.5 and GPT4, for the domain of chip testing. A key aspect of chip design is functio…
C2HLSC: Leveraging Large Language Models to Bridge the Software-to-Hardware Design Gap
Luca Collini, Siddharth Garg, Ramesh Karri
High-Level Synthesis (HLS) tools offer rapid hardware design from C code, but their compatibility is limited by code constructs. This paper investigates Large Language Models (LLMs…
Masala-CHAI: A Large-Scale SPICE Netlist Dataset for Analog Circuits by Harnessing AI
Jitendra Bhandari, Vineet Bhat, Yuheng He +3
Masala-CHAI is a fully automated framework leveraging large language models (LLMs) to generate Simulation Programs with Integrated Circuit Emphasis (SPICE) netlists. It addresses a…
Automatically Improving LLM-based Verilog Generation using EDA Tool Feedback
Jason Blocklove, Shailja Thakur, Benjamin Tan +3
Traditionally, digital hardware designs are written in the Verilog hardware description language (HDL) and debugged manually by engineers. This can be time-consuming and error-pron…