{"id":"W4296433611","doi":"10.1007/978-3-031-15922-0_5","title":"Towards Automatic OpenMP-Aware Utilization of Fast GPU Memory","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Compiler; Parallel computing; Reuse; Shared memory; Memory management; Computer architecture; Operating system; Embedded system; Semiconductor memory","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001073604,0.0004875767,0.0006617143,0.001119227,0.0003148219,0.000286619,0.004349173,0.0002305001,0.0002060053],"category_scores_gemma":[0.00009151181,0.0004690636,0.0001596479,0.001085384,0.0004416399,0.0006187703,0.002660593,0.000633356,0.00001411674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003219377,"about_ca_system_score_gemma":0.0008951871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004225195,"about_ca_topic_score_gemma":0.00001115426,"domain_scores_codex":[0.9961131,0.0000892887,0.0007695922,0.001251963,0.001297366,0.0004787181],"domain_scores_gemma":[0.9972001,0.0002401004,0.0005914433,0.001508604,0.0003357389,0.0001240116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002501103,0.00004115852,0.00001159207,0.0000856916,0.00001146657,0.00002919582,0.0008957476,0.1972367,0.00002058129,0.01430386,0.0001104368,0.7872511],"study_design_scores_gemma":[0.0001768482,0.0001880512,0.00005341745,0.0002808824,0.000007595822,0.00004437667,4.065491e-7,0.965374,0.001780254,0.03048878,0.001106936,0.0004984576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00002645197,0.0003319415,0.986372,0.0003228986,0.001077604,0.0004687481,0.000008495528,0.0005142528,0.01087762],"genre_scores_gemma":[0.1125263,0.0001343537,0.8854398,0.0009236246,0.0001750581,0.00002480082,0.00002766316,0.00005810673,0.0006903137],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7867526,"threshold_uncertainty_score":0.9997761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02897981077577515,"score_gpt":0.2776855436521747,"score_spread":0.2487057328763996,"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."}}