{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001565165,0.00006818162,0.00006939982,0.00006511594,0.0001975326,0.00008209509,0.0005650932,0.00003341803,0.00004955177],"category_scores_gemma":[0.00001712902,0.00004034784,0.00003043862,0.0001509824,0.00002321979,0.0003807781,0.0004034155,0.00003344186,0.0001113604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002515934,"about_ca_system_score_gemma":0.00002640728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001264512,"about_ca_topic_score_gemma":0.000001732005,"domain_scores_codex":[0.9993069,0.00004540557,0.0001241955,0.0002123197,0.0001180537,0.0001931508],"domain_scores_gemma":[0.9994087,0.00008136001,0.00003722056,0.0003606423,0.0000555838,0.00005651482],"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":[0.000002298255,0.00007312931,0.0005122681,0.00000273882,0.00001124454,0.000002519638,0.00009217597,0.002725745,0.006947155,0.842739,0.05739847,0.08949327],"study_design_scores_gemma":[0.001998927,0.0002241466,0.01035478,0.0004382007,0.000009963906,0.00006604603,0.00003164107,0.6796978,0.05982342,0.1855216,0.06041852,0.001414949],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004170509,0.00003117976,0.9800097,0.003315589,0.0001113204,0.00005895634,2.624051e-7,0.0010596,0.0149963],"genre_scores_gemma":[0.6727542,0.00001928401,0.324125,0.0005223559,0.00002197877,0.000005588554,3.072568e-7,0.000004557734,0.00254672],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6769721,"threshold_uncertainty_score":0.1645337,"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."}}