The BIDS ecosystem comprises an impressive network of Fellows, including some who are Berkeley Lab scientists. This month, several Berkeley Lab-BIDS Fellows are organizing two of events to share their data-science expertise: Machine Learning for Science (ML4Sci) Workshop and the California Water Data Hackathon.
High School Summer Student is 'Posit-ive' About Coding
Educating for Exascale
ESS-DIVE: A Game Changer for Environmental Research
Tess Smidt, 'Atomic Architect'
Berkeley Lab Joins Exascale Machine Learning Effort
Results from a collaboration between the Exascale Computing Project's Sparse Solvers Software Technology project and ExaGraph Co-Design Center showed that the parallel AWPM (approximate-weight perfect matching) code can run up to 2,500x faster than the sequential algorithm on 256 nodes of NERSC's Cori supercomputer.
In a plenary talk given at the recent CHEP conference, NERSC and CRD researchers presented findings from a study in which they demonstrated how generative adversarial networks can speed simulations in high energy physics studies.
Sanjana Shah, a high school student from the Peninsula discovered her passion for programming when she attended a coding workshop for youth sponsored by a local tech company. She is also the first (and so far, the only) high school student CRD's David Donofrio has ever hired through the Computing Sciences Summer Student program.