{"id":"W2052113320","doi":"10.1109/asap.2014.6868644","title":"A case against small data types in GPGPUs","year":2014,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Menzies School of Health Research; University of Victoria","keywords":"Computer science; Stencil; Cache; Parallel computing; Latency (audio); Cache pollution; Data access; Distributed computing; CPU cache; Cache algorithms; Database; Computational science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004178819,0.00006293551,0.00007975437,0.00008361016,0.00003986595,0.00008590781,0.0009704854,0.00003169815,0.000003637956],"category_scores_gemma":[0.00007960567,0.00005490863,0.00001002222,0.0002227547,0.00001140272,0.0001754961,0.0005772954,0.00006430229,0.00002769476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008967584,"about_ca_system_score_gemma":0.00002005566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001005694,"about_ca_topic_score_gemma":0.0001251711,"domain_scores_codex":[0.9993372,0.00006175628,0.000127993,0.0002820947,0.00005770521,0.0001332791],"domain_scores_gemma":[0.9989395,0.00006668572,0.00002962169,0.0009012664,0.00002431747,0.00003860238],"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":[0.000006286619,0.0002612821,0.00283567,0.00003156465,0.00001727048,0.001345312,0.0008207997,0.03220495,0.0001032369,0.179972,0.02477699,0.7576246],"study_design_scores_gemma":[0.0001030133,0.00001539117,0.00005520811,0.000006566253,5.206412e-7,0.0001176082,0.000002359288,0.9931592,0.0001491559,0.0008750316,0.005427495,0.00008850309],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006296554,0.00002159191,0.9669247,0.000288821,0.00006727633,0.00004951971,5.217399e-7,0.0004197594,0.02593122],"genre_scores_gemma":[0.5353721,0.00000691172,0.4637222,0.0006029984,0.00002037794,0.00000155798,0.000004357887,0.000003098634,0.0002664104],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9609542,"threshold_uncertainty_score":0.2239109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06468676438864937,"score_gpt":0.2754711283403823,"score_spread":0.2107843639517329,"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."}}