{"id":"W2180959024","doi":"10.1109/tmag.2010.2081662","title":"Enhancing the Performance of Conjugate Gradient Solvers on Graphic Processing Units","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Magnetics","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Conjugate gradient method; Computer science; Conjugate; Parallel computing; Computational science; Matrix (chemical analysis); Algorithm; Mathematics; Materials science","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":[0.001061075,0.001002172,0.000805106,0.0005793988,0.0005015229,0.001347403,0.000994556,0.001022382,0.003999657],"category_scores_gemma":[0.008640599,0.0004362851,0.0004431485,0.001011846,0.000827028,0.001579902,0.001281187,0.001557587,0.001481279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004656259,"about_ca_system_score_gemma":0.001407322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002755537,"about_ca_topic_score_gemma":0.003079608,"domain_scores_codex":[0.9991335,0.0003180986,0.0000366571,0.00005311987,0.0003634238,0.00009514995],"domain_scores_gemma":[0.9973246,0.001612385,0.0001375742,0.0003240422,0.0005217385,0.0000797143],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001057371,0.0002106143,0.003044714,0.0007843115,0.0001290381,0.0005856449,0.0005074653,0.5072778,0.0814083,0.07191195,0.01466289,0.31842],"study_design_scores_gemma":[0.00003163571,0.00005483089,0.0002077024,0.00001682229,0.000009016609,0.00005638778,0.00001819211,0.9747314,0.01692972,0.004643394,0.003289151,0.00001162767],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04605804,0.0007159803,0.9409506,0.0007247265,0.0001961494,0.00008462397,0.00005482932,0.002744728,0.008470306],"genre_scores_gemma":[0.3471429,0.0006519871,0.6466522,0.000246919,0.0001000493,0.0001321716,0.000145918,0.0007948811,0.004132968],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003999657,"threshold_uncertainty_score":0.01338017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02388422119664639,"score_gpt":0.2120530118419275,"score_spread":0.1881687906452811,"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."}}