For their collaborative project “Acceleration of Deep Neural Networks via Heterogeneous Computing for Real-Time Processing of Neutrino and Particle-Trace Imagery,” Luca Carloni of the Computer Science Department and Georgia Karagiorgi of the Department of Physics were among the five teams awarded funding through the Research Initiatives in Science and Engineering (RISE) competition. Created in 2004, RISE is one of the largest internal research grant competitions within the University, and each year provides funds for interdisciplinary faculty teams from the basic sciences, engineering, and medicine to explore paradigm-shifting and high-risk ideas. This year 29 teams presented pre-proposals; of the nine teams asked to submit full proposals, five were selected to receiving funding in the amount of $80,000 per year for up to two years.
Carloni and Karagiorgi were awarded funding to develop machine learning techniques and to explore deep neural network implementations for “listening” to only the most important and rare physics signals while disregarding environmental noise and other accidental background signals. To do so, they will build a data processing system that can facilitate real-time processing and accurate classification of images streamed at rates on the order of terabytes per second. The primary target application is the future Deep Underground Neutrino Experiment (DUNE). This is a major international particle physics experiment that will be operational in the US for more than a decade, beginning in 2024, and will be continually streaming high-resolution 3D images of the active detector region at a total data rate exceeding 5 terabytes per second. The ability to process this data in real time and to efficiently identify and accurately classify interesting activity in the detector would enable the discovery of rare particle interactions that have never been observed before. This ability however requires the development of an advanced data processing system. This RISE project aims to develop a scalable heterogeneous computing system that employs machine learning for identification and classification of interesting activity in the data. The ultimate goal is to leverage recent advancements in computer science to render the DUNE experiment a powerfully sensitive instrument for fundamental particle physics discovery.
“We are in the midst of a Big Data revolution, wherein our capacity to generate data greatly exceeds our ability to analyze and make sense of everything,” says Karagiorgi. “In my own discipline of particle physics, we think that there is a great deal of information hidden in astroparticle data sets, such as those that will be recorded by the DUNE experiment. But we will need advanced methods and powerful systems to scan through those data sets and efficiently and accurately fish out the information we care about. This project requires interdisciplinary collaboration between physics and computer science, and time – afforded by RISE – to explore our early-stage ideas. If we can develop a system for only capturing the most important data, this is a project that can feasibly capture the attention of the National Science Foundation or the Department of Energy.”
The seed money provided by RISE allows teams to more fully develop high-risk, high-reward ideas to better pursue other avenues of funding. Since 2004, RISE has awarded $9.62 million to 72 projects. These 72 teams later secured more than $55.4 million from governments and private foundations: a 600% return on Columbia’s initial investment. These projects have additionally garnered more than 130 peer-reviewed publications and educated more than 130 postdoctoral scholars and graduate, undergraduate, and high school students.
Applications for the 2019 competition run from September to early-October 2018, with five to six awarded teams announced by spring 2019. Beginning in September, visit the RISE website to apply.