Argonne physicists are using Mira to perform simulations of Large Hadron Collider (LHC) experiments with a leadership-class supercomputer for the first time, shedding light on a path forward for interpreting future LHC data. Researchers at the Argonne Leadership Computing Facility (ALCF) helped the team optimize their code for the supercomputer, which has enabled them to simulate billions of particle collisions faster than ever before.
At CERN's Large Hadron Collider (LHC), the world's most powerful particle accelerator, scientists initiate millions of particle collisions every second in their quest to understand the fundamental structure of matter.
With each collision producing about a megabyte of data, the facility, located on the border of France and Switzerland, generates a colossal amount of data. Even after filtering out about 99 percent of it, scientists are left with around 30 petabytes (or 30 million gigabytes) each year to analyze for a wide range of physics experiments, including studies on the Higgs boson and dark matter.
To help tackle the considerable challenge of interpreting all this data, researchers from the U.S. Department of Energy's (DOE's) Argonne National Laboratory are demonstrating the potential of simulating collision events with Mira, a 10-petaflops IBM Blue Gene/Q supercomputer at the Argonne Leadership Computing Facility (ALCF), a DOE Office of Science User Facility.
"Simulating the collisions is critical to helping us understand the response of the particle detectors," said principal investigator Tom LeCompte, an Argonne physicist and the former physics coordinator for the LHC's ATLAS experiment, one of four particle detectors at the facility. "Differences between the simulated data and the experimental data can lead us to discover signs of new physics."
This marks the first time a leadership-class supercomputer has been used to perform massively parallel simulations of LHC collision events. The effort has been a great success thus far, showing that such supercomputers can help drive future discoveries at the LHC by accelerating the pace at which simulated data can be produced. The project also demonstrates how leadership computing resources can be used to inform and facilitate other data-intensive high energy physics experiments.
http://www.eurekalert.org/pub_releases/2015-11/dnl-aht110315.php
