Session

Description The Large Hadron Collider (LHC) is the "energy frontier" of high energy physics, but the accelerator itself has advanced fundamental physics only with extensive computing resources and R&D. Data collection from the detectors around LHC's collision sites require advanced GPU- and FPGA-based triggers to filter the incoming data. Simulating the creation of known particles from hypothetical physics requires GPU-accelerated quantum chromodynamics (QCD). Modeling those particles' interaction with the detectors to create simulated responses requires massive compute resources that are being gradually transitioned to GPUs. Finally, confirming new physics requires complex analysis frameworks that reconstruct experimental particle tracks and compare them with the simulated results to deduce the fundamental physics creating those particles. Our minisymposium will dive into the advanced computing necessary to enable these new discoveries: a big-picture overview of the LHC, the detector experiments, their cumulative computing requirements; high-level descriptions of the R&D in GPU accelerators and AI/ML, "online" computing for filtering and capturing data from the experiments, "offline" computing for event generation and detector simulation, and "reconstruction" that determines new physics by comparing the experimental and computational results.