Yunsong Wang earned his Ph.D. from Maison de la Simulation of CEA Saclay and École Polytechnique in the area of high-performance computing in December 2017 under the supervision of Dr. Christophe Calvin, Fausto Malvagi and Emeric Brun. His thesis work focused on the optimization of Monte Carlo neutron transport calculations by using many-core architectures. He received his Diplôme d'Ingénieur (equivalent to M.S.) from Polytech Paris-UPMC in November 2014 and his B.S. degree from Huazhong University of Science and Technology in July 2012.
Yunsong joined NERSC as a NESAP for Data Postdoctoral Fellow in January 2018 and is working on performance optimization of ATLAS workflows on Cori.
High-performance computing, multi-threading, vectorization, GPGPU, Monte Carlo transport,
Wang, Y., Hugot, F. X., Brun, E., Malvagi, F., & Calvin, C. (2017). Efficient Cross Section Reconstruction on Modern Multi and Many Core Architectures. In International Conference on Parallel Processing and Applied Mathematics(pp. 90-100). Springer, Cham.
Wang, Y., Brun, E., Malvagi, F., & Calvin, C. (2017). Competing energy lookup algorithms in Monte Carlo neutron transport calculations and their optimization on CPU and Intel MIC architectures. Journal of Computational Science, 20, 94-102.
Wang, Y., Brun, E., Malvagi, F., & Calvin, C. (2016). Competing Energy Lookup Algorithms in Monte Carlo Neutron Transport Calculations and Their Optimization on CPU and Intel MIC Architectures. Procedia Computer Science, 80, 484-495.