{"id":"W2161873733","doi":"10.1109/tpwrs.2010.2042084","title":"SIMD-Based Large-Scale Transient Stability Simulation on the Graphics Processing Unit","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Power Systems","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":107,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"SIMD; Graphics processing unit; Computer science; Transient (computer programming); Graphics; Computation; Parallel computing; Computational science; General-purpose computing on graphics processing units; Software; Stability (learning theory); Central processing unit; CUDA; Computer hardware; Computer graphics (images); Algorithm; Operating system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008380229,0.0003011981,0.0002764353,0.0001680267,0.000405844,0.0001456556,0.0002249635,0.0002281379,0.0002193689],"category_scores_gemma":[0.00001299992,0.0002344574,0.000173295,0.0005751659,0.00007908989,0.0001742218,4.976511e-7,0.0006841695,0.00004332713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007941879,"about_ca_system_score_gemma":0.00006070096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001921213,"about_ca_topic_score_gemma":0.0003251193,"domain_scores_codex":[0.9980773,0.0001931983,0.0005388081,0.0003524769,0.0004742214,0.0003639836],"domain_scores_gemma":[0.9985018,0.0003346802,0.00006968516,0.0007497238,0.0001977168,0.0001463939],"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":[0.00003775191,0.0002430278,0.00005816299,0.0001448682,0.00002249938,5.64681e-7,0.001214379,0.9971569,0.0008909169,0.00009628995,0.00005536564,0.00007933632],"study_design_scores_gemma":[0.0004621588,0.000086927,0.0002141299,0.0000719567,0.00002422518,0.000001714311,0.0004613691,0.9861698,0.003610528,0.000004986138,0.008618412,0.0002738053],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08762228,0.00002689738,0.9047477,0.0001161477,0.002923569,0.000875931,0.0001529662,0.000589891,0.002944651],"genre_scores_gemma":[0.9995674,0.000001551804,0.00006691128,0.0000981179,0.00001037854,0.0001384604,0.000006549721,0.00005553949,0.00005510536],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9119451,"threshold_uncertainty_score":0.9560896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01985382580772502,"score_gpt":0.2372271881753037,"score_spread":0.2173733623675787,"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."}}