{"id":"W4388760782","doi":"10.17760/d20581919","title":"Towards efficient deep neural network inference and training for ubiquitous AI","year":2023,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Crossbar switch; Resistive random-access memory; Artificial intelligence; Deep learning; Scalability; Computer architecture; Computer engineering; Distributed computing; Machine learning; Engineering","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":[0.0008161957,0.000784562,0.0006269129,0.0004481402,0.0003277808,0.001176823,0.001718668,0.0009679571,0.003306125],"category_scores_gemma":[0.002673268,0.0006500946,0.0005972141,0.0006779904,0.0005996564,0.002061827,0.001380255,0.002804069,0.001177045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001055413,"about_ca_system_score_gemma":0.001322196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00439266,"about_ca_topic_score_gemma":0.009510597,"domain_scores_codex":[0.9995486,0.00009574585,0.00002757596,0.00009306666,0.0001746856,0.00006036629],"domain_scores_gemma":[0.9994075,0.0002788036,0.00004121509,0.0001078161,0.0001345495,0.00003011521],"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":[0.0001355304,0.0001115929,0.000780359,0.0002905549,0.00009239562,0.00008462428,0.0001203251,0.6223272,0.01564323,0.04988241,0.006469999,0.3040618],"study_design_scores_gemma":[0.000005435675,0.00001311516,0.00004864691,0.00001059884,0.000005114693,0.000008308295,0.000008804531,0.9872262,0.001706925,0.00924373,0.001720368,0.000002792272],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.005605808,0.0006296292,0.9902412,0.0003796594,0.00004757263,0.00003229724,0.00006263074,0.0009677482,0.002033347],"genre_scores_gemma":[0.1986569,0.001420336,0.7948779,0.000405328,0.00008544222,0.0002086537,0.0003390257,0.0003023645,0.003703919],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.00439266,"threshold_uncertainty_score":0.01106006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03333344622705265,"score_gpt":0.3057634321185062,"score_spread":0.2724299858914535,"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."}}