{"id":"W2625482784","doi":"10.29069/forscience.2016v4n1.e164","title":"Avaliação de desempenho e consumo energético para configurações de Wavefront pools de uma GPU AMD","year":2016,"lang":"pt","type":"article","venue":"ForScience","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"","keywords":"Computer science; Energy consumption; Power consumption; Parallel computing; Computational science; Physics; Power (physics)","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":[0.002484677,0.0004735899,0.0004604559,0.0002723949,0.0007334265,0.0006782379,0.00305043,0.0002794755,0.0001491401],"category_scores_gemma":[0.0009160282,0.0003778351,0.0001982646,0.0007620458,0.0008091476,0.0008073956,0.0006233497,0.0002775149,0.000268212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000607813,"about_ca_system_score_gemma":0.001543401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003745522,"about_ca_topic_score_gemma":0.00004426895,"domain_scores_codex":[0.9951819,0.0005088614,0.0006493859,0.001117506,0.0006972367,0.001845118],"domain_scores_gemma":[0.9967869,0.0006382588,0.0004086611,0.001144971,0.0003101682,0.0007110226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002483146,0.001415758,0.05537486,0.0003825769,0.0002327584,0.0007520801,0.03216164,0.02429345,0.2242212,0.191777,0.1214937,0.3476467],"study_design_scores_gemma":[0.001193915,0.0005968299,0.01515606,0.001034525,0.00005236888,0.0004834939,0.0001836617,0.7892011,0.1652822,0.01341703,0.01189566,0.001503125],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05679556,0.0004660557,0.936651,0.00241641,0.0004554264,0.0003260844,0.00002343759,0.0006439103,0.002222106],"genre_scores_gemma":[0.836189,0.0003499306,0.1536718,0.001450018,0.0001161926,0.00004376928,0.000001718397,0.00002904898,0.008148559],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7829792,"threshold_uncertainty_score":0.9998674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03497611583631578,"score_gpt":0.2943089933915203,"score_spread":0.2593328775552045,"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."}}