{"id":"W2497380202","doi":"10.1109/ipdpsw.2016.196","title":"Employing Compression Solutions under OpenACC","year":2016,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Speedup; Parallel computing; CUDA; Bandwidth (computing); Memory bandwidth; Programming paradigm; Interconnection; Memory model; Shared memory; Programming language; Computer network","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004548066,0.001070541,0.0004286522,0.0006540848,0.000586362,0.001167357,0.001691042,0.0008182664,0.005847193],"category_scores_gemma":[0.002846999,0.000323287,0.0004235727,0.0009916235,0.0006236117,0.001402987,0.001317827,0.001110211,0.001974967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006515643,"about_ca_system_score_gemma":0.001167187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003751569,"about_ca_topic_score_gemma":0.003501894,"domain_scores_codex":[0.9995491,0.00007151135,0.00002789089,0.00007211629,0.0002153831,0.00006390174],"domain_scores_gemma":[0.9987858,0.0002853101,0.0001296836,0.0003196855,0.0004231563,0.00005641067],"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":[0.000757408,0.000421209,0.004571854,0.0005530363,0.0001154306,0.0007647091,0.0006081958,0.2185092,0.05044858,0.08717912,0.02583642,0.6102349],"study_design_scores_gemma":[0.00008709001,0.0001419912,0.0009516221,0.00004901809,0.00003541283,0.0003142167,0.00007628112,0.9053478,0.03491415,0.02611275,0.03192982,0.0000397607],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08377022,0.0005154167,0.8448705,0.0005953151,0.0003057374,0.0001974551,0.0003003496,0.02656323,0.04288176],"genre_scores_gemma":[0.4036207,0.0003755304,0.5765326,0.0003855781,0.0001892506,0.0004028543,0.001091068,0.003431108,0.01397129],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005847193,"threshold_uncertainty_score":0.01956081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05156253628962067,"score_gpt":0.288854681847988,"score_spread":0.2372921455583674,"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."}}