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Video: Heterogeneous Computing at the Large Hadron Collider

Philip Harris from MIT

In this video, Philip Harris from MIT presents: Heterogeneous Computing at the Large Hadron Collider.

Only a small fraction of the 40 million collisions per second at the Large Hadron Collider are stored and analyzed due to the huge volumes of data and the compute power required to process it. This project proposes a redesign of the algorithms using modern machine learning techniques that can be incorporated into heterogeneous computing systems, allowing more data to be processed and thus larger physics output and potentially foundational discoveries in the field.

Philip Harris joined the MIT faculty in 2017. Born in Sao Paulo, he received his B.S in Physics from Caltech in 2005, and his Ph.D from MIT in 2011 on research performed at CERN with the CMS experiment. From 2011-2013, Philip was a CERN fellow working on the Higgs discovery. From 2014-2017, he was a CERN staff scientist working on the CMS experiment.

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