{"id":"W3088770438","doi":"10.1145/3407904","title":"Approximate Cache in GPGPUs","year":2020,"lang":"en","type":"article","venue":"ACM Transactions on Embedded Computing Systems","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Computer science; Cache; Parallel computing; Cache algorithms; Cache pollution; Cache invalidation; Cache coloring; Smart Cache; Cache-oblivious algorithm; Page cache; Thread (computing); CPU cache; Operating system","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":[0.0002352343,0.0004841347,0.0005951126,0.0004738896,0.0005814011,0.001292511,0.001938841,0.0007241764,0.00757656],"category_scores_gemma":[0.001287437,0.0002919406,0.0002903576,0.001353163,0.0004145215,0.001664495,0.0009414016,0.0009916476,0.001709769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009849272,"about_ca_system_score_gemma":0.001126329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004643768,"about_ca_topic_score_gemma":0.006528725,"domain_scores_codex":[0.9995854,0.00006468435,0.00001919905,0.00005500402,0.0002111258,0.00006458333],"domain_scores_gemma":[0.9996227,0.00008548789,0.00002991384,0.00009776012,0.0001312241,0.00003295229],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001542542,0.000279652,0.006706675,0.001226308,0.0002235403,0.001096598,0.0006143037,0.3247052,0.03599023,0.1104009,0.168428,0.348786],"study_design_scores_gemma":[0.0002025614,0.0004290761,0.001211439,0.0001393504,0.00008669796,0.0004120836,0.0001535628,0.8066587,0.02047306,0.03536737,0.1347815,0.0000845829],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2311357,0.02549034,0.6037973,0.003875633,0.001471193,0.000469934,0.002216031,0.02343505,0.1081087],"genre_scores_gemma":[0.7846879,0.003725392,0.1867566,0.0017767,0.0001596958,0.0005312538,0.002210314,0.0008639534,0.01928817],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00757656,"threshold_uncertainty_score":0.0253461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03449785459226638,"score_gpt":0.2679640858403253,"score_spread":0.2334662312480589,"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."}}