{"id":"W2049554599","doi":"10.1016/j.compeleceng.2013.05.013","title":"Recalling instructions from idling threads to maximize resource utilization for simultaneous multi-threading processors","year":2013,"lang":"en","type":"article","venue":"Computers & Electrical Engineering","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"National Science Foundation","keywords":"Threading (protein sequence); Computer science; Resource (disambiguation); Parallel computing; Chemistry; Computer network","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001632448,0.0002818053,0.0003194874,0.0003817578,0.0002432161,0.0003920069,0.000846555,0.0001378015,0.000002301015],"category_scores_gemma":[0.0004562383,0.0003051184,0.00009807671,0.00121512,0.00001187705,0.0003700113,0.0001906738,0.0002491511,0.00001336249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001599911,"about_ca_system_score_gemma":0.00003982232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003399263,"about_ca_topic_score_gemma":7.820738e-7,"domain_scores_codex":[0.9980781,0.00002976111,0.0004406841,0.0006551308,0.0002289807,0.0005673609],"domain_scores_gemma":[0.9983259,0.0007177845,0.0001014445,0.0003821475,0.0002275062,0.0002452052],"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":[0.00000575623,0.00003247346,0.00002300011,0.00001391574,0.00001988333,0.00000196261,0.0002910829,0.9079895,0.001114108,0.001199144,0.0002928019,0.08901639],"study_design_scores_gemma":[0.0003284926,0.00009877451,0.00006552292,0.00008952482,0.000007832019,0.000008143797,0.000003693306,0.9933714,0.003768538,0.0004793195,0.001418076,0.0003607436],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008097218,0.0001642463,0.9886602,0.000274696,0.0002910259,0.000671274,0.000001640452,0.001815361,0.00002433285],"genre_scores_gemma":[0.2755556,0.000009457452,0.7239069,0.0002189691,0.0001365927,0.00009403475,0.00001356564,0.00003380165,0.00003102409],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2674584,"threshold_uncertainty_score":0.9999401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02702744636915749,"score_gpt":0.2545608825208572,"score_spread":0.2275334361516997,"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."}}