Paola A. Buitrago leads the Artificial Intelligence and Big Data group at the Pittsburgh Supercomputing Center (PSC), which is a joint effort of Carnegie Mellon University and the University of Pittsburgh. Her group is focused on advancing and supporting the convergence of High Performance Computing (HPC), Artificial Intelligence (AI) and Big Data. Paola is the principal investigator (PI) for the upcoming NSF-funded ($5M) Neocortex, a specialized supercomputer that is designed to revolutionize national AI-enabled research by incorporating specialized AI-hardware (Cerebras CS-1). She is also PI for Open Compass, a new platform for AI research on emerging hardware and software technologies, enabling the development of advanced algorithms and modeling approaches, and co-PI for Bridges and Bridges-2, two large multipurpose supercomputers at PSC. Bridges-2 ($10M) will be deployed by PSC in late 2020. Paola’s diverse background includes research in deep learning, large scale data, and workflow management for high energy physics experiments at the Fermi National Accelerator Laboratory. Paola’s academic background includes a Bachelors degree in Chemical Engineering and a Bachelors in Systems and Computing Engineering. She holds a Masters from Universidad de los Andes in Bogotá, Colombia.

Topic: Accelerating AI for Data-Driven Scientific Discovery

• Nicholas A. Nystrom, Chief Scientist, Pittsburgh Supercomputing Center & Carnegie Mellon University
• Paola A. Buitrago, Director, AI & Big Data, Pittsburgh Supercomputing Center & Carnegie Mellon University

Artificial Intelligence (AI) is enabling great breakthroughs across research, yet its computational needs are outpacing mainstream computing. How can we continue to drive the breakthroughs we need to combat pandemics, develop effective treatments for cancer and rare diseases, protect the environment, and create a sustainable future? Our approach at the Pittsburgh Supercomputing Center brings together revolutionary computer architecture that rejects previously assumed constraints to achieve unprecedented levels of performance for specific domains, coupled with general-purpose high-performance computing (HPC) and high-performance data analytics (HPDA). We describe Neocortex, a highly innovative system designed to introduce the Cerebras CS-1 and Wafer Scale Engine – the largest processor ever built with 1.2 trillion transistors and 400,000 cores – to the research community, and moreover, to enable scaling ambitious deep learning training across multiple CS-1 systems by leveraging a 24 TB HPE Superdome Flex as an unusually capable “front end”. We also describe Bridges-2, another new supercomputer with which Neocortex will be closely federated to provide large-scale data management, preprocessing, and complementary simulation capabilities. Both systems will be available at no cost for open research.