Huihuo Zheng is a Computer Scientist in the datascience group. His research interests include data management and parallel I/O, large scale distributed training. He applies high performance computing and deep learning to various domain sciences, such as physics, chemistry and material sciences. He also co-lead the MLPerf Storage Benchmarking group in developing benchmark suites for evaluating the performance of storage system for AI applications.
Huihuo received his PhD. in Physics at the University of Illinois at Urbana-Champaign in 2016. He has a strong background in condensed matter physics, first-principle simulations with density functional theory and Quantum Monte Carlo. He joined ALCF as a Theta Early Science postdoc in 2016, working on developing and scaling density functional theory and many-body perturbation theory. He then joined the datascience group in 2018, expanding his expertises in data science and machine learning.
His current projects include: (1) ExaIO/ExaHDF5 - developing advanced features in the HDF5 library for efficient parallel I/O, such as caching and presaging on node-local storage, topology-aware collective I/O; (2) data management and I/O for AI workloads; (3) scalable image reconstruction algorithm development.
Huihuo's Google Scholar page: https://scholar.google.com/citations?user=dd7fUtEAAAAJ&hl=en