Jonathan C. McKinney is the research director at H2O.ai. He was a professor in physics at the University of Maryland at College Park where he created new numerical models, algorithms, and code to simulate astrophysical plasmas and black holes to test Einstein's theories. He used machine learning through-out his research, and now applies himself at H2O.ai to develop its latest machine learning algorithms on GPUs. He also contributes to other projects like DriverlessAI. In his free time he goes mountain climbing (e.g. Uhuru peak on Kilimanjaro), hiking, biking, and spending time with his family.
GPU Accelerated Machine Learning
Deep learning algorithms have benefited greatly from the recent performance gains of GPUs. However, it has been unclear whether GPUs can speed up machine learning algorithms such as generalized linear modeling, random forests, gradient boosting machines, and clustering. H2O.ai, the leading open source AI company, is bringing the best-of-breed data science and machine learning algorithms to GPUs. We introduce H2O4GPU, a fully featured machine learning library that is optimized for GPUs with a robust python API that is drop dead replacement for scikit-learn. We'll demonstrate benchmarks for the most common algorithms relevant to enterprise AI and showcase performance gains as compared to running on CPUs.