Stage Set for Richer Machine Learning-Infused HPC

A research collaboration between the National Cancer Institute (NCI) and Lawrence Livermore National Laboratory (LLNL) is demonstrating the value of using machine learning to overcome daunting computational challenges. Although the specific goal of NCI-LLNL work is to advance the understanding of the biomolecular mechanisms that underly some of the most aggressive human cancers, the computational approach that was employed to do this has more far-reaching application. At least that's the claim of Fred Streitz, LLNL's Chief Computational Scientist and HPC Innovation Center Director, who led the project at the national lab. According to Streitz, the collaboration was very much in the interest of both organizations: NCI reaped the direct benefit of advancing their cancer research work, while LLNL got the opportunity to explore new ways of using machine learning to cut intractable HPC problems down to size. "It turns out that the workflows that are necessary to understand some of these biology problems are different than what we are currently doing," Streitz told The Next Platform.