Enabling High Energy Physics at the Information Frontier Using GPUs and Other Many/Multi-Core Architectures

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High energy physics (HEP) experiments use extremely large data sets to study the fundamental constituents of matter and the forces that govern their interactions. To use computing resources most effectively, the investigators will study algorithms and develop codes that run well on computers which provide especially high performance for parallel execution of instructions, including general purpose graphics processing units (GPUs) and other many-core/multi-core architectures. These studies, and the community tools to be developed here, will extend the quantitative reach in HEP and allied fields to the point where they enable qualitative advances. To enhance the broader impact of this work, the investigators will distribute the statistical analysis toolkit as Free and Open Source Software. In addition, the investigators will disseminate their results about effectively writing GPU-friendly algorithms via talks, short courses, and journal articles.The specific HEP context for this project will be developing tools for analyzing data from the next generation of experiments. The last major elements of the Standard Model (SM) of particle physics (which describes the electromagnetic, weak nuclear, and strong nuclear interactions of fundamental particles) have been experimentally validated in the past decade. Detailed measurements of particle-antiparticle asymmetries in the decays of B-mesons by the BABAR and Belle collaborations led to Kobayashi and Maskawa sharing the 2008 Nobel Prize in Physics. The ATLAS and CMS experiments at CERN discovered a Higgs-like boson in 2012, leading to Englert and Higgs sharing the 2013 Nobel prize in physics. The codes and toolkits to be developed here will enable HEP experiments to search more effectively for phenomena not described by the SM, sometimes called Beyond-the-Standard-Model (BSM) physics. ATLAS and CMS are searching for direct evidence of BSM physics at the highest energies. Belle-II, the next generation electron-positron flavor factory being built in Japan, has a design luminosity two orders of magnitude greater than that of Belle, providing complementary BSM sensitivity in very high statistics studies of B-meson decays, charm mixing, and searches for lepton flavor violation. The LHCb experiment at CERN has already surpassed BaBar and Belle by more than an order of magnitude in many channels, and the resulting BSM constraints complement those from ATLAS and CMS. Analyzing the data from all these experiments will require disproportionately more computing power at a modest increase in cost. In addition to developing generally useful tools, the statistical analysis toolkit developed here will be applied to analyze data from LHCb.