{"id":"W4406265540","doi":"10.1109/sips62058.2024.00009","title":"MemNAS: Super-net Neural Architecture Search for Memristor-based DNN Accelerators","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Memristor; Computer science; Architecture; Artificial neural network; Computer architecture; Artificial intelligence; Engineering; Electronic 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001000652,0.0001881045,0.0001521284,0.0001147452,0.00008931561,0.00007769994,0.0001570705,0.00006399381,0.00008647747],"category_scores_gemma":[0.0000137241,0.0001584979,0.0001121478,0.0002171624,0.00001990516,0.0001148144,0.00002443523,0.0003136215,0.0000204754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005850927,"about_ca_system_score_gemma":0.00002266864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002077793,"about_ca_topic_score_gemma":0.000006421139,"domain_scores_codex":[0.9990758,0.00001706529,0.0001623853,0.0002529181,0.0001236933,0.0003681243],"domain_scores_gemma":[0.9994508,0.0002617015,0.000004337108,0.0001638139,0.00002139571,0.00009793345],"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":[0.00003580392,0.00001260411,0.00003385094,0.0007887686,0.00004447376,0.00004839543,0.0003227384,0.8386825,0.09789046,0.001057347,0.008212525,0.05287054],"study_design_scores_gemma":[0.0002872943,0.0001036789,0.00002356772,0.00005810498,0.00001607383,0.00001509183,0.00005893635,0.6064706,0.345143,0.0003063079,0.04716679,0.0003504621],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7246464,0.00148215,0.264455,0.0005593074,0.002431016,0.0005574992,0.00002651778,0.002795862,0.003046157],"genre_scores_gemma":[0.9957669,0.000004682763,0.003070551,0.0001865551,0.0003661549,0.00002564675,0.00001782435,0.00006472062,0.0004969504],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2711205,"threshold_uncertainty_score":0.6463356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02480787702623328,"score_gpt":0.2677612228997359,"score_spread":0.2429533458735026,"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."}}