Marc Casas is a senior researcher at the Barcelona Supercomputing Center (BSC). His research focuses on the analysis and simulation of high-performance computing systems, on improving computer architectures and parallel systems via accurate prediction methodologies, and on computer arithmetic for deep learning workloads. He is the main creator of the MUltiscale-Simulation Approach (MUSA), a simulation and analysis tool for large-scale systems and applications. He leads BSC's contribution to the Mont-Blanc2020 project and research collaborations with Intel and IBM. Marc has been at BSC since 2013. He was a postdoctoral research scholar at the Lawrence Livermore National Laboratory (LLNL) from 2010 to 2013. He received the Marie Curie and Ramón y Cajal Fellowships on 2014 and 2018, respectively. He received a 5-years degree in mathematics in 2004, and a PhD degree in Computer Science in 2010 from the Universitat Politècnica de Catalunya (UPC).
Parallel Programming Languages and Models