{"id":"W2134616937","doi":"10.1145/1596655.1596670","title":"Automatic parallelization for graphics processing units","year":2009,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Parallel computing; Speedup; Just-in-time compilation; Graphics; Control flow; Compiler; General-purpose computing on graphics processing units; Bytecode; Java; CUDA; Java bytecode; Optimizing compiler; Programming language; Operating system; Java applet; Java annotation","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":[0.0001750418,0.00007907992,0.00008419309,0.0001078629,0.000157289,0.0001622982,0.0003634928,0.00004341835,0.000002171992],"category_scores_gemma":[0.00005653538,0.0000701975,0.00002283407,0.0006529498,0.000009159027,0.0003221915,0.00002267041,0.00003558708,0.000002020281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001043673,"about_ca_system_score_gemma":0.00005627264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001126914,"about_ca_topic_score_gemma":4.337426e-7,"domain_scores_codex":[0.9993759,0.00001954527,0.0001633315,0.00018182,0.0001091186,0.0001503273],"domain_scores_gemma":[0.9994466,0.00003055892,0.00006905458,0.0001916571,0.0002231598,0.00003897503],"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":[0.000001604481,0.00005262313,0.00004188855,0.00002436453,0.000003291954,6.519887e-7,0.0003455428,0.005638873,0.0000462345,0.5426624,0.007365261,0.4438173],"study_design_scores_gemma":[0.0001204286,0.00007397115,0.000297537,0.00001901659,0.000001782909,0.000002802829,0.00000272654,0.9668623,0.0004958406,0.03079119,0.001229974,0.0001023874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005104882,0.00005552888,0.9944016,0.001117836,0.0000334328,0.0001845215,1.588262e-7,0.001533222,0.002163247],"genre_scores_gemma":[0.3975683,0.000009028553,0.6010585,0.001168728,0.00001820563,0.000008088861,0.000004370506,0.000003212242,0.0001615615],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9612235,"threshold_uncertainty_score":0.2862571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02984482087482458,"score_gpt":0.2850426655707745,"score_spread":0.2551978446959499,"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."}}