{"paper":{"title":"GRay: a Massively Parallel GPU-Based Code for Ray Tracing in Relativistic Spacetimes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.IM","authors_text":"2), (2) Nordic Institute for Theoretical Physics, 3, 3), (3) Institute for Theory, 4) ((1) Department of Astronomy, (4) Radcliffe Institute for Advanced Study, Chi-kwan Chan (1, Computation, Dimitrios Psaltis (1, Feryal Ozel (1, Harvard-Smithsonian Center for Astrophysics, Harvard University), University of Arizona","submitted_at":"2013-03-20T20:00:30Z","abstract_excerpt":"We introduce GRay, a massively parallel integrator designed to trace the trajectories of billions of photons in a curved spacetime. This GPU-based integrator employs the stream processing paradigm, is implemented in CUDA C/C++, and runs on nVidia graphics cards. The peak performance of GRay using single precision floating-point arithmetic on a single GPU exceeds 300 GFLOP (or 1 nanosecond per photon per time step). For a realistic problem, where the peak performance cannot be reached, GRay is two orders of magnitude faster than existing CPU-based ray tracing codes. This performance enhancement"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1303.5057","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}