{"id":"W4392412748","doi":"10.1109/swc57546.2023.10448789","title":"Mixed-Precision Architecture for GPU Tensor Cores","year":2023,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Computer science; Tensor (intrinsic definition); Architecture; Parallel computing; Computational science; Mathematics; Geometry","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":[0.0003608838,0.0006646519,0.0003631839,0.0006116976,0.0004510412,0.0009353658,0.00199325,0.0004227184,0.006042855],"category_scores_gemma":[0.001224845,0.0003114494,0.0003462701,0.0008143224,0.0003272566,0.001147279,0.0006598718,0.0007223419,0.001302655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001139321,"about_ca_system_score_gemma":0.001061915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004423982,"about_ca_topic_score_gemma":0.008230156,"domain_scores_codex":[0.9996276,0.00005015859,0.00003194285,0.00008500848,0.0001434178,0.00006178138],"domain_scores_gemma":[0.9995487,0.00005791832,0.00004017107,0.0001114269,0.000202957,0.00003884272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001966066,0.0002701778,0.00769399,0.0007547834,0.0002703895,0.0006593837,0.00043103,0.1668127,0.1242057,0.08745448,0.05429366,0.5551878],"study_design_scores_gemma":[0.0001312143,0.0005769581,0.00124014,0.00007590552,0.00009844916,0.0004033144,0.00007031094,0.8889613,0.05268047,0.01518279,0.04050946,0.00006967814],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.161084,0.002769477,0.7896066,0.0007623651,0.0004989928,0.0002017371,0.0006026061,0.01184105,0.03263323],"genre_scores_gemma":[0.6939629,0.0004494701,0.2943504,0.0003194092,0.00005450037,0.0001689813,0.0006886087,0.0002372458,0.009768477],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006042855,"threshold_uncertainty_score":0.02021539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03494900415742708,"score_gpt":0.2876714994407456,"score_spread":0.2527224952833185,"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."}}