2017/05/17 by Derek Weitzel, Weitzel, Derek, Brian Bockelman +9
Computer Science · Decision Sciences · #Advanced Data Storage Technologies #Distributed #Distributed and Parallel Computing Systems #FOS: Computer and information sciences #FOS: Physical sciences #Instrumentation and Methods for Astrophysics (astro-ph.IM) #Parallel #Scientific Computing and Data Management #and Cluster Computing (cs.DC)
paper · pdf · doi:10.48550/arxiv.1705.06202
openalex publication_date 2017/05/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
During 2015 and 2016, the Laser Interferometer Gravitational-Wave Observatory (LIGO) conducted a three-month observing campaign. These observations delivered the first direct detection of gravitational waves from binary black hole mergers. To search for these signals, the LIGO Scientific Collaboration uses the PyCBC search pipeline. To deliver science results in a timely manner, LIGO collaborated with the Open Science Grid (OSG) to distribute the required computation across a series of dedicated, opportunistic, and allocated resources. To deliver the petabytes necessary for such a large-scale computation, our team deployed a distributed data access infrastructure based on the XRootD server suite and the CernVM File System (CVMFS). This data access strategy grew from simply accessing remote storage to a POSIX-based interface underpinned by distributed, secure caches across the OSG.