Co-Designing Intelligent Cyberinfrastructure for Computing Continuum: Overview of the Activities at the NSF-AI Institute ICICLE

Remote event

Artificial intelligence (AI) is transforming every sector of society. However, there is a massive and ever-growing gap between available AI techniques and their availability to end users across a range of application domains. This talk will start with an overview of the ICICLE (Intelligent CyberInfrastructure (CI) with Computational Learning in the Environment), an NSF-AI Institute, to address these challenges. We will demonstrate how ICICLE seeks to be the first and foremost edge-to-center AI-as-a-service enterprise for the emerging computing continuum, advancing foundational AI research by fostering next-gen CI for AI to support the wholesome democratization of AI through responsible plug-and-play, and extending the usability and usefulness of AI to the wider population. An overview of the co-designing activities at the institute spanning multiple directions, CI (high performance computing, networking), AI (statistical machine learning, computer vision, knowledge graphs, model commons and conversational AI), data privacy and trust, and three leading use-inspired sciences (Animal Ecology, Digital Agriculture, and Smart Foodsheds) will be highlighted. Overall, the talk will demonstrate the feasibility of co-designing intelligent CI for AI which can be easily adapted to various parts of the computing continuum and serve multiple use-inspired domains.

Instructor

Dhabaleswar K. (DK) Panda

Professor and University Distinguished Scholar, Ohio State University.

Dhabaleswar K. (DK) Panda is a Professor and University Distinguished Scholar of Computer Science and Engineering at the Ohio State University. He is serving as the Director of the ICICLE NSF-AI Institute (https://icicle.ai). He has published over 500 papers. The MVAPICH MPI libraries, designed and developed by his research group (http://mvapich.cse.ohio-state.edu), are currently being used by more than 3,475 organizations worldwide (in 93 countries). More than 1.97 million downloads of this software have taken place from the project's site. This software is empowering many clusters in the TOP500 list. High-performance and scalable solutions for Deep Learning frameworks and Machine Learning applications from his group are available from https://hidl.cse.ohio-state.edu. Similarly, scalable, and high-performance solutions for Big Data and Data science frameworks are available from https://hibd.cse.ohio-state.edu. Prof. Panda is a Fellow of ACM and IEEE. He is a recipient of the 2022 IEEE Charles Babbage Award and the 2024 IEEE TCPP Outstanding Service and Contributions Award. More details about Prof. Panda are available at http://www.cse.ohio-state.edu/~panda.