{"id":"W2115676933","doi":"10.1109/hpca.2009.4798270","title":"A first-order fine-grained multithreaded throughput model","year":2009,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Cache; Parallel computing; Multithreading; Throughput; Thread (computing); Cache algorithms; Markov chain; CPU cache; Probabilistic logic; Cache invalidation; Multi-core processor; Operating system","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":[0.0001321628,0.0001453357,0.0001455458,0.00008617524,0.0001487029,0.0001211928,0.0007069195,0.00006849979,0.00001334823],"category_scores_gemma":[0.00004762146,0.0001232599,0.00005661323,0.000422126,0.00001881966,0.0003167204,0.0001072877,0.00009317221,0.0000377231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002165978,"about_ca_system_score_gemma":0.0000459526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001639752,"about_ca_topic_score_gemma":0.000009733309,"domain_scores_codex":[0.9989876,0.00001927277,0.0002002205,0.0003542359,0.0001809272,0.0002577846],"domain_scores_gemma":[0.9991809,0.00003559176,0.0000547298,0.0005330094,0.0001250074,0.00007075667],"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":[0.000006559529,0.0001936587,0.00004005326,0.000005229587,0.00001008525,0.000007188812,0.000849424,0.6747946,0.0001463638,0.2714711,0.03624689,0.01622879],"study_design_scores_gemma":[0.0002529606,0.00005966876,0.00009964442,0.000009061364,0.000001492925,0.000004515787,0.000001615653,0.9706051,0.0006798583,0.02729809,0.0008132069,0.0001747499],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002020789,0.00003802855,0.972251,0.005756373,0.00004520083,0.0001276002,3.639176e-7,0.001685297,0.01989407],"genre_scores_gemma":[0.2354853,0.00001115798,0.7603974,0.001835812,0.00002281229,0.00000491756,0.000001630374,0.000004683604,0.002236297],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2958105,"threshold_uncertainty_score":0.5026394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02480541939593741,"score_gpt":0.2719134931181629,"score_spread":0.2471080737222255,"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."}}