{"id":"W2149265311","doi":"10.1109/icpp.2007.33","title":"Design, Implementation, and Evaluation of Trellis-SDP for File-Level Data Parallelism","year":2007,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Parallel Processing","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Trellis (graph); Parallel computing; Parallelism (grammar); Data parallelism; Simple (philosophy); Programming paradigm; Overlay; Software; Programming language; Theoretical computer science; Distributed computing; Algorithm","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003459402,0.0009331302,0.0006674821,0.0006910273,0.0007484359,0.00179161,0.005223304,0.0009607176,0.005186553],"category_scores_gemma":[0.007906387,0.0008718872,0.00082969,0.00104629,0.001292015,0.002544258,0.001550438,0.002577461,0.001969776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001602653,"about_ca_system_score_gemma":0.003197048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004712483,"about_ca_topic_score_gemma":0.003328468,"domain_scores_codex":[0.9964823,0.0005997327,0.0002842834,0.0004479038,0.001741875,0.0004440471],"domain_scores_gemma":[0.9938898,0.001417168,0.0003211321,0.00136513,0.002399055,0.0006078205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004197148,0.002335054,0.01240097,0.001862109,0.0004781279,0.00210669,0.001962958,0.08222102,0.2026505,0.05011418,0.08096362,0.5587077],"study_design_scores_gemma":[0.001207993,0.001576174,0.003265941,0.0001091612,0.0001534125,0.0006739766,0.0002295102,0.5967027,0.3107902,0.007593221,0.07751539,0.000182237],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07993019,0.0004027613,0.8293193,0.0005841784,0.0002919624,0.001807938,0.0006059082,0.07192371,0.01513405],"genre_scores_gemma":[0.2698897,0.0002905034,0.7092908,0.0004101117,0.00007587367,0.001094894,0.00182335,0.006796397,0.01032839],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005223304,"threshold_uncertainty_score":0.01829535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2670058010561064,"score_gpt":0.3966202846173962,"score_spread":0.1296144835612899,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}