Many of today's most important applications rely on high-performance manipulation of matrices, tensors, and general arrays of data. The neural networks at the heart of AI language models are a prime example. The AI software stack relies on kernels (e.g., for matrix-matrix product) that are specifically designed to deliver throughput close to the hardware's theoretical peak. However, writing kernels that can deliver maximum performance is extremely challenging. In this talk, I will discuss some of the work we have done to simplify the task of authoring such kernels. This includes new abstractions to allow for algebraic manipulation of array layouts and new programming models for more easily expressing the kernels themselves.
Michael Garland has been a researcher at NVIDIA since 2006. He joined the company as one of the founding members of NVIDIA Research and is currently Senior Director of Programming Systems Research. He leads a research group focused on developing technologies that will help programmers take advantage of modern high-performance machines. Their work spans the software stack with a particular focus on parallel algorithms, programming languages, compilers and runtime systems, and low-level hardware/software interfaces. He and his team have both published numerous academic articles and contributed to many software packages in broad use by CUDA developers.
This seminar presents a synthesis of research focused on leveraging these data sources for infectious disease prediction, spanning from classical statistical approaches to modern AI architectures.
The talk aims to offer perspective on when and how statistical rigor and deep learning flexibility each contribute to reliable disease forecasting.
Dr. Shihao Yang is the Harold E. Smalley Early Career Professor and Assistant Professor in the School of Industrial and Systems Engineering at Georgia Tech. He completed his PhD in statistics and post-doc in Biomedical Informatics at Harvard University. Dr. Yang’s research focuses on data science, with special interest in time series, dynamical systems, and applications in infectious disease transmission forecasting.
To attend, please register online via Zoom.
]]>This landmark edition will begin in Albi, where the pre-conference on June 5–6 will bring together PhD students, researchers, and industry professionals for interactive training sessions, including the “My Thesis in 180 Seconds” challenge, and immersive learning experiences using cutting-edge Virtual Reality games. The event will then move to Bordeaux from June 8–10 for the main conference, themed “Supply Chain and Logistics Intelligence in the Era of the Physical Internet: Bridging High-Tech and Low-Tech Solutions.”
Participants will enjoy a vibrant program featuring scientific and industrial sessions, inspiring keynotes, dynamic roundtables, exhibitions, company visits, and collaborative workshops designed to foster innovation and shape the future of logistics and supply chain networks.
And, because logistics is global, participants will be from all over the world including researchers, industrial and international institution members, local authorities and standardization committees.
About the Physical Internet Initiative
The Physical Internet Initiative aims at transforming the way physical objects are moved, stored, realized, supplied and used, pursuing global logistics efficiency and sustainability. Originating from Professor Benoit Montreuil in 2006, this ground breaking vision, revolutionizing current paradigms, has stirred great interest from scientific, industrial as well as governmental communities.