{"id":"W1995519297","doi":"10.2118/163661-ms","title":"Developement of Algebraic Multigrid Solvers Using GPUs","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures; CMG Reservoir Simulation Foundation; University of Calgary; Nvidia","keywords":"Multigrid method; Solver; Computer science; Discretization; Computational science; Algebraic number; Parallel computing; Applied mathematics; Mathematics; Partial differential equation","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005080765,0.00007838754,0.0001207847,0.00003953898,0.00001401715,0.000005683663,0.00007662384,0.00002257756,0.0002597116],"category_scores_gemma":[0.00006799633,0.00007026818,0.00002517269,0.0001204763,0.00002159501,0.00008826391,0.0000262955,0.00004590577,0.00004003166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004409164,"about_ca_system_score_gemma":0.000007215006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006792776,"about_ca_topic_score_gemma":2.130681e-7,"domain_scores_codex":[0.9994811,0.000009244411,0.0002142593,0.00006524316,0.0001152341,0.000114899],"domain_scores_gemma":[0.9995838,0.0002046007,0.00002783578,0.00009078767,0.00005503051,0.00003794943],"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":[0.000001021153,0.00003355592,0.0002250163,0.0001943703,0.00006696412,7.565198e-7,0.0002555091,0.8861935,0.04231617,0.004876056,0.0004180084,0.06541909],"study_design_scores_gemma":[0.0001239472,0.00000932517,0.0004747057,0.00002449082,0.000005664509,0.000002235622,0.00007193231,0.928283,0.03829805,0.03236618,0.0002045964,0.0001359164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.130349,0.00002853136,0.867622,0.000009780958,0.0001418227,0.0001156871,5.66281e-7,0.00009777004,0.00163489],"genre_scores_gemma":[0.2697293,0.000003047039,0.7301926,0.00002248914,0.00001247433,0.000006435752,4.140039e-7,0.0000130539,0.00002021007],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1393803,"threshold_uncertainty_score":0.2865453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03214665048476448,"score_gpt":0.280183879585568,"score_spread":0.2480372291008035,"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."}}