{"id":"W7133087510","doi":"","title":"Impact of FPGA Architectures on Area and Performance of CGRA Overlays","year":2020,"lang":"","type":"dissertation","venue":"TSpace","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Field-programmable gate array; Leverage (statistics); Architecture; Overlay; Performance improvement","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":[0.0004888158,0.0005705705,0.000242795,0.0003274557,0.00023617,0.0008115616,0.0007907882,0.0003639986,0.00292483],"category_scores_gemma":[0.001843519,0.0001975352,0.0002721588,0.0002977566,0.0003360003,0.001157914,0.0005504534,0.0003863646,0.0004092465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005353224,"about_ca_system_score_gemma":0.0003283018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001005854,"about_ca_topic_score_gemma":0.001760768,"domain_scores_codex":[0.9994051,0.0001145082,0.00002651816,0.0001030377,0.0002247645,0.0001259845],"domain_scores_gemma":[0.9988229,0.000555765,0.0001437795,0.000275773,0.0001545055,0.00004721111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008857558,0.0001491791,0.004954663,0.000325753,0.00007407853,0.0005183247,0.0001842321,0.7304596,0.1571759,0.007050943,0.001717991,0.09650356],"study_design_scores_gemma":[0.00008252354,0.002350961,0.005929691,0.00006070425,0.0001027139,0.0005552815,0.0002670167,0.7194085,0.2543692,0.004339537,0.01248018,0.00005376263],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9366633,0.0006931809,0.04117304,0.0001694207,0.00007393253,0.00004023646,0.000140367,0.001569863,0.01947679],"genre_scores_gemma":[0.9802516,0.0001307128,0.01805577,0.00002998126,0.000007528829,0.00001459305,0.00008810126,0.0001174817,0.001304378],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.00292483,"threshold_uncertainty_score":0.00978452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02698740628452994,"score_gpt":0.3345761978167221,"score_spread":0.3075887915321922,"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."}}