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Biography
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 obtained a 5-years degree in mathematics in 2004, and a PhD degree in Computer Science in 2010 from the Universitat Politècnica de Catalunya (UPC).
Presentations
Paper
Machine Learning, Deep Learning and Artificial Intelligence
Requirements, Performance, and Benchmarks
Reliability and Resiliency
TP
Paper
Accelerators, FPGA, and GPUs
Fault Tolerance
Power
Reliability and Resiliency
TP
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