We explore how the function as a service paradigm can be used to address the computing challenges in experimental high-energy physics at CERN. As a case study, we use funcX—a high-performance function as a service platform that enables intuitive, flexible, efficient, and scalable remote function execution on existing infrastructure—to parallelize an analysis operating on columnar data to aggregate histograms of analysis products of interest in real-time. We demonstrate efficient execution of such analyses on heterogeneous resources.
A case study in preserving a high energy physics application with Parrot
