{"paper":{"title":"The Anatomy of Large-Scale Distributed Graph Algorithms","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DS","cs.PF","cs.SE"],"primary_cat":"cs.DC","authors_text":"Andrew Lumsdaine, Jesun Sahariar Firoz, Marcin Zalewski, Martina Barnas, Thejaka Amila Kanewala","submitted_at":"2015-07-23T23:42:34Z","abstract_excerpt":"The increasing complexity of the software/hardware stack of modern supercomputers results in explosion of parameters. The performance analysis becomes a truly experimental science, even more challenging in the presence of massive irregularity and data dependency. We analyze how the existing body of research handles the experimental aspect in the context of distributed graph algorithms (DGAs). We distinguish algorithm-level contributions, often prioritized by authors, from runtime-level concerns that are harder to place. We show that the runtime is such an integral part of DGAs that experimenta"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1507.06702","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"}