Program Synthesis Tools for Scientific Computing

Program Synthesis Tools for Scientific Computing

This project is to develop a program synthesis tool for applications in Scientific Computing. Specifically, we will use program synthesis methods to take mathematical algorithm descriptions as input and produce functionally correct and performant code. We will develop...
Efficient Diffusion Models for Scientific Machine Learning

Efficient Diffusion Models for Scientific Machine Learning

Recently, diffusion models have emerged as a powerful new family of deep generative models with record- breaking performance in many applications. However, due to the intensive requirements of data and computational resources, diffusion models suffer from limitations...
Resilient Distributed Training of Large Models

Resilient Distributed Training of Large Models

Large language models (LLMs) and generative AI (GenAI), are taking the world by storm. These large deep neural network (DNN) models are predominantly trained in large GPU clusters on ever-growing datasets using a combination of parallelism techniques, including data...