Dr. Costa is a Research Staff Member at IBM T. J. Watson Research Center, where he is part of the Data-Centric Solutions (DCS) department. His research is mainly focused on system software, programming models and middleware for next-generation high-performance analytics systems, working at the intersection of traditional HPC and emerging large-scale big data analytics workloads. His work also includes novel methods for software/hardware cooperation to improve system resiliency.
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 systems. Currently, he is leading efforts in the design and development of a converged software platform for data analytics, bridging the gap between emerging paradigms for distributed computing, such as Cloud computing, and traditional HPC platforms. He has made contributions showing how big data analytics frameworks like Apache Spark can be optimized in an HPC platform, and how advanced features and HPC technology can be used to scale and accelerate workflows in the areas of machine learning and genomics. He has been involved in multiple projects with clients and partners.
He received his Ph.D and M.Sc. degrees in computer engineering from University of Sao Paulo (Brazil) and his B.Sc. degree in computational physics from University of Brasilia (Brazil).