Deep learning for fundamental sciences using high-performance computing (O’Reilly AI Conference)
The fundamental sciences (including particle physics and cosmology) generate exabytes of data from complex instruments and analyze these to uncover the secrets of the universe. Deep learning is enabling the direct exploitation of higher-dimensional instrument data than previously possible, so improving the sensitivity for new discoveries. In this talk, our guest speaker Wahid Bhimji (NERSC) describes recent activity in this field, particularly that at NERSC, the mission supercomputing centre for US fundamental science, based at Berkeley National Lab. This work exploits and builds on Tensorflow to explore novel methods and applications; exploit high-performance computing scales; and provide productive deep learning environments for fundamental scientists.
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