{"id":"W2470680602","doi":"10.1109/hotchips.2008.7476518","title":"Scalable parallel programming with CUDA introduction","year":2008,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"CUDA; Computer science; Multithreading; Parallel computing; Scalability; General-purpose computing on graphics processing units; Yarn; Software; Programming paradigm; Computer architecture; Computational science; Thread (computing); Operating system; Graphics; Programming language","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":[0.0001161983,0.00009044858,0.00009250668,0.00007309351,0.00021074,0.0000729413,0.0003312383,0.00003077249,0.00001351012],"category_scores_gemma":[0.00001074575,0.00006841419,0.00002106282,0.0004092379,0.00004632041,0.0003763638,0.00007750531,0.00007658899,0.0000318989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001937513,"about_ca_system_score_gemma":0.00004192947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002637268,"about_ca_topic_score_gemma":0.000002010748,"domain_scores_codex":[0.999189,0.0000256537,0.0001199745,0.000294122,0.0001722172,0.0001990285],"domain_scores_gemma":[0.9994387,0.00001238332,0.00004755613,0.0003509874,0.00009611135,0.00005428608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007192943,0.000797692,0.01610747,0.00004682347,0.00009670068,0.0001314438,0.002351416,0.1855442,0.0002521768,0.3085329,0.2631634,0.2229038],"study_design_scores_gemma":[0.001002264,0.000718696,0.0024394,0.00002694074,0.000007547601,0.0009638177,0.00003256715,0.7653534,0.007237747,0.001939661,0.2194184,0.0008595606],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001693485,0.00003012542,0.990281,0.001470428,0.00006793231,0.0001178615,3.197877e-8,0.001364937,0.004974194],"genre_scores_gemma":[0.1053752,0.00001874479,0.8913625,0.0001419597,0.0001106937,0.00001537009,0.000001676909,0.00000578243,0.002967966],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5798092,"threshold_uncertainty_score":0.278985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01470627592782548,"score_gpt":0.2278957640372783,"score_spread":0.2131894881094528,"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."}}