6 papers
SOLAR: AI-Powered Speed-of-Light Performance Analysis
Qijing Huang, Sana Damani, Zhifan Ye +9
How fast could a deep-learning model run on target hardware, and how far is today's implementation from that limit? These questions are central to software, hardware, and algorithm…
SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits
Edward Lin, Sahil Modi, Siva Kumar Sastry Hari +30
As agentic AI systems become increasingly capable of generating and optimizing GPU kernels, progress is constrained by benchmarks that reward speedup over software baselines rather…
FNODE: Flow-Matching for data-driven simulation of constrained multibody systems
Hongyu Wang, Jingquan Wang, Dan Negrut
Data-driven modeling of constrained multibody dynamics remains challenged by (i) the training cost of Neural ODEs, which typically require backpropagation through an ODE solver, an…
SimBench: A Framework for Evaluating and Diagnosing LLM-Based Digital-Twin Generation for Multi-Physics Simulation
Jingquan Wang, Andrew Negrut, Hongyu Wang +2
We introduce SimBench, a benchmark designed to evaluate the proficiency of simulator-oriented LLMs (S-LLMs) in generating digital twins (DTs) that can be used in simulators for vir…
ChronoLLM: Customizing Language Models for Physics-Based Simulation Code Generation
Jingquan Wang, Andrew Negrut, Harry Zhang +5
This contribution is concerned with the following issue: can pretrained large language models (LLMs) be refined and customized to the point where they become virtual assistants hel…
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono
Jingquan Wang, Harry Zhang, Khailanii Slaton +4
Recently, the integration of advanced simulation technologies with artificial intelligence (AI) is revolutionizing science and engineering research. ChronoLlama introduces a novel…