{"id":"W4400677064","doi":"10.3390/computers13070174","title":"A Comprehensive Review of Processing-in-Memory Architectures for Deep Neural Networks","year":2024,"lang":"en","type":"review","venue":"Computers","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Artificial neural network; Computer science; Computer architecture; Artificial intelligence; Neuroscience; Cognitive science; Psychology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003130632,0.00112206,0.0006511605,0.001337153,0.0002153891,0.0007178902,0.0008243843,0.0008624028,0.00658531],"category_scores_gemma":[0.0008238417,0.0004290458,0.0005088547,0.001542091,0.0001843265,0.001342963,0.0004951481,0.0009358542,0.003017588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003897716,"about_ca_system_score_gemma":0.001201623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001103176,"about_ca_topic_score_gemma":0.002057375,"domain_scores_codex":[0.9998587,0.00001704729,0.0000203284,0.00002893572,0.00006004237,0.00001486338],"domain_scores_gemma":[0.9997646,0.0001010115,0.0000288076,0.00001118617,0.00008166278,0.00001273278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003992364,0.00005679691,0.0001890391,0.01742545,0.00008427464,0.0001119392,0.00004403368,0.002847634,0.004835804,0.009434415,0.03174831,0.9331824],"study_design_scores_gemma":[0.000007405507,0.0001430449,0.0003431646,0.002902604,0.0001383971,0.0004773064,0.00002777581,0.002070212,0.003700431,0.004358151,0.9858036,0.0000280014],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0009418332,0.9806597,0.008041546,0.0005607798,0.0004860868,0.00003004402,0.0002112457,0.0001243841,0.008944442],"genre_scores_gemma":[0.005012777,0.9835649,0.005713634,0.0004187589,0.0002953243,0.0000483872,0.000348041,0.00002618294,0.004571892],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.00658531,"threshold_uncertainty_score":0.02203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03881419212555036,"score_gpt":0.3212293180190555,"score_spread":0.2824151258935051,"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."}}