{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009226603,0.0004974804,0.001775671,0.0002038132,0.00003121928,0.00001988515,0.0003671749,0.0001349263,0.000001594133],"category_scores_gemma":[0.00001553592,0.0004115205,0.0005495041,0.0004585752,0.00004690976,0.00002293053,0.0001128244,0.000626136,0.00000229467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006148921,"about_ca_system_score_gemma":0.0000251226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.305585e-7,"about_ca_topic_score_gemma":4.136675e-7,"domain_scores_codex":[0.9983369,0.00005694555,0.0007615642,0.0003802782,0.0001029964,0.0003613452],"domain_scores_gemma":[0.9991893,0.00028971,0.0001558145,0.0002588851,0.00004076972,0.00006554989],"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":[0.000001004468,0.000002780373,1.690793e-8,0.3296395,0.00002112787,0.00001442342,0.00001674624,0.09208834,1.329117e-7,0.000001446731,0.0001349949,0.5780795],"study_design_scores_gemma":[0.0001114969,0.00004229723,3.339823e-7,0.2608955,0.0003879995,0.00009856634,0.000002594866,0.4556503,0.000001142764,0.00003550193,0.2823268,0.0004474201],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000007777691,0.9621657,0.03517742,0.000005985402,0.001190653,0.00117031,0.000008703289,0.000244913,0.00002852657],"genre_scores_gemma":[0.00007850518,0.9969291,0.002258779,0.0001197878,0.0003659535,0.00009190644,0.00004146097,0.0001092415,0.000005236845],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.5776321,"threshold_uncertainty_score":0.9998336,"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."}}