{"id":"W2149003795","doi":"10.1109/micro.2008.4771779","title":"Hybrid analytical modeling of pending cache hits, data prefetching, and MSHRs","year":2008,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Menzies School of Health Research","keywords":"Computer science; Cache; Superscalar; Parallel computing; Cache algorithms; Locality; Locality of reference; CPU cache","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":[0.0003133459,0.00008252102,0.0001420722,0.00009263973,0.0001101528,0.0000372402,0.0008555695,0.00002437202,0.000006541946],"category_scores_gemma":[0.00006280669,0.00007227136,0.00001865008,0.0001173368,0.00003533911,0.000395372,0.0008346845,0.00008859871,0.000001566244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008660979,"about_ca_system_score_gemma":0.00004100756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008510907,"about_ca_topic_score_gemma":8.854244e-7,"domain_scores_codex":[0.9990931,0.00003682813,0.0002181865,0.0003388808,0.0001688444,0.0001441954],"domain_scores_gemma":[0.9991166,0.00005051584,0.00005312989,0.0006714677,0.00004554167,0.00006271615],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002550897,0.0003998003,0.0116237,0.0001317148,0.0001645624,0.000110856,0.003456274,0.7606387,0.0002894937,0.1459748,0.02220036,0.05498422],"study_design_scores_gemma":[0.0000825122,0.00001750737,0.00007711336,0.00001200775,0.000003443064,0.00005601425,0.000005776502,0.9986902,0.000290181,0.0005820922,0.00009440411,0.00008869586],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03186995,0.0001062404,0.9631113,0.0001309537,0.00002827048,0.00004889318,0.000001699416,0.0002488614,0.00445379],"genre_scores_gemma":[0.6707379,0.00006467517,0.329046,0.00004441856,0.0000116945,3.958615e-7,0.000004613773,0.000003228578,0.00008701303],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.638868,"threshold_uncertainty_score":0.2947141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1002529723987607,"score_gpt":0.3034855556939368,"score_spread":0.2032325832951761,"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."}}