Abstract: Emerging computing workflows in science and industry combine traditional large-scale simulation, AI and data analytics to enable faster and more accurate results or radically new solutions. From emerging and fundamentally new paradigms in AI, such as the emergence of Foundation Models, to the challenges of integrating new computing paradigms like quantum computing, these workflows bring unprecedented challenges and opportunities for the computing platform. Hear how IBM Research is addressing these challenges by re-imagining the computing platform and building a converged solution for these workloads. The talk will include an overview of our approach for Foundation Models, from building a cloud-native supercomputing infrastructure, to a simplified, cloud-native common stack to run large scale workloads in multi-cloud environment, to applying this full stack to a wide range of domains.
Speaker Bio: Dr. Carlos Costa is a Principal Research Staff Member at IBM T. J. Watson Research Center, where he leads efforts to build a next-generation platform for AI/ML and HPC workflows. His research is mainly focused on system software, programming models and middleware for next-generation distributed systems, working at the intersection of traditional HPC and emerging distributed computing paradigms. He has been involved in multiple projects in the areas of HPC and analytics, including the BlueGene/Q system, the Active Memory Cube (AMC) architecture for in-memory processing, and DoE ORNL’s Summit and LLNL’s Sierra supercomputer systems, among other projects with clients and academic partners.