{"id":"W2915521883","doi":"10.1145/3289602.3294002","title":"Enhancing Butterfly Fat Tree NoCs for FPGAs with Lightweight Flow Control","year":2019,"lang":"en","type":"article","venue":"","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Router; Field-programmable gate array; Network on a chip; Embedded system; Deflection routing; Latency (audio); Place and route; Network packet; Scheduling (production processes); Computer network; Routing protocol; Static routing; 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":[0.0002390103,0.0001459261,0.0002405691,0.00006180655,0.00008965327,0.0002063376,0.0004094455,0.00006351805,0.00005833582],"category_scores_gemma":[0.00000624136,0.0000945945,0.00008820526,0.0001334221,0.000009049288,0.0003683798,0.00003484456,0.00007267964,0.0002065686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003458824,"about_ca_system_score_gemma":0.00002518081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000282919,"about_ca_topic_score_gemma":0.0002913404,"domain_scores_codex":[0.9988592,0.00003680259,0.0002383765,0.0003758607,0.0001744704,0.0003153206],"domain_scores_gemma":[0.999126,0.0001697894,0.00007895919,0.000444829,0.0001096853,0.00007075249],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008466091,0.000494785,0.00881393,0.0005147992,0.00102509,0.00006978868,0.007724032,0.0201641,0.08854828,0.6431427,0.1193274,0.1093285],"study_design_scores_gemma":[0.002250621,0.0006246773,0.0001064915,0.0001030513,0.00001034509,0.00004191114,0.0000597357,0.9225684,0.02753094,0.0004171735,0.04595123,0.000335382],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01136388,0.00003115622,0.9731247,0.0009360571,0.001311937,0.0005338429,0.00000126436,0.0001536501,0.01254349],"genre_scores_gemma":[0.9604291,7.889213e-7,0.02551341,0.00117918,0.0003850866,0.00005677033,0.000001258905,0.00001272707,0.01242173],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9490651,"threshold_uncertainty_score":0.3857452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006146486900138345,"score_gpt":0.196263460002829,"score_spread":0.1901169731026906,"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."}}