{"id":"W2091928261","doi":"10.1016/j.future.2011.04.001","title":"Power-aware linear programming based scheduling for heterogeneous computer clusters","year":2011,"lang":"en","type":"article","venue":"Future Generation Computer Systems","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Scheduling (production processes); Energy consumption; Homogeneous; Power consumption; Distributed computing; Power (physics); Mathematical optimization","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":[0.0006913333,0.0005136533,0.0007109471,0.0003683027,0.0006958389,0.0008596076,0.001321672,0.0004017787,0.002632345],"category_scores_gemma":[0.001505966,0.000449306,0.0003814726,0.0007879569,0.0003945348,0.0007993277,0.0007193413,0.0007621083,0.0002900386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009257517,"about_ca_system_score_gemma":0.001148212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004589073,"about_ca_topic_score_gemma":0.01159312,"domain_scores_codex":[0.9995661,0.0001676519,0.00001427609,0.00005942798,0.0001111629,0.00008130948],"domain_scores_gemma":[0.9993843,0.0003468737,0.00005508533,0.0000514432,0.0001074329,0.00005491161],"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":[0.0001638834,0.00007257171,0.0002879784,0.00005146748,0.00002127799,0.00003497078,0.00003998738,0.9626119,0.003647588,0.004480276,0.001284923,0.02730314],"study_design_scores_gemma":[0.000009938281,0.00001888719,0.00004813125,8.472413e-7,0.000003519596,0.000003703147,0.000007510213,0.9976539,0.0004771738,0.001588602,0.0001860964,0.000001802635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07151208,0.0004421748,0.9184178,0.0004498511,0.0001017511,0.00006983874,0.0000604132,0.0008079867,0.008138144],"genre_scores_gemma":[0.8073037,0.000201144,0.1864697,0.0001296372,0.00007454868,0.0001133039,0.0001142311,0.0002441999,0.005349466],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004589073,"threshold_uncertainty_score":0.009124756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03719703718312911,"score_gpt":0.2429635761190709,"score_spread":0.2057665389359418,"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."}}