{"id":"W2073600756","doi":"10.1145/2423636.2423642","title":"Thermal-aware task scheduling in 3D chip multiprocessor with real-time constrained workloads","year":2013,"lang":"en","type":"article","venue":"ACM Transactions on Embedded Computing Systems","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":118,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Computer science; Multiprocessing; Scheduling (production processes); Parallel computing; Computation; Chip; Dynamic priority scheduling; Fair-share scheduling; Distributed computing; Architecture; Multiprocessor scheduling; Embedded system; Two-level scheduling; Real-time computing; Algorithm; Computer network; Quality of service","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":[0.0002876672,0.0003672598,0.0003374098,0.0001954675,0.0003135073,0.0003692674,0.0006343899,0.0003119091,0.0004638123],"category_scores_gemma":[0.001005951,0.0002380691,0.0002933513,0.0003362507,0.0002987575,0.0004660013,0.0003105593,0.0003122221,0.00009283274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005030411,"about_ca_system_score_gemma":0.0008314691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004690877,"about_ca_topic_score_gemma":0.004483032,"domain_scores_codex":[0.9997836,0.00007624063,0.000009444915,0.0000328355,0.00004596072,0.00005189821],"domain_scores_gemma":[0.9996425,0.0001539168,0.00006376197,0.0000462511,0.00005447768,0.00003909694],"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":[0.00006680046,0.00002386969,0.0005360091,0.00001552161,0.000008522476,0.00004409753,0.00002479126,0.9866389,0.00534019,0.001179026,0.0002581071,0.005864302],"study_design_scores_gemma":[0.000002669916,0.00001095419,0.0001132022,4.875e-7,0.000001291036,0.00000449983,0.000003938977,0.9989725,0.0004884992,0.0003231387,0.00007716582,0.000001686366],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5986319,0.0005782879,0.3954606,0.0003158531,0.0000669217,0.00003750839,0.00008364535,0.0006040999,0.004221174],"genre_scores_gemma":[0.9790413,0.00009431307,0.02037721,0.00003920209,0.000008873214,0.00002341107,0.00003423241,0.00003419033,0.0003472482],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004690877,"threshold_uncertainty_score":0.009327173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01219602355206222,"score_gpt":0.2411095779338136,"score_spread":0.2289135543817514,"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."}}