{"id":"W2184134753","doi":"10.82308/7410","title":"Optimization techniques for distributed Verilog simulation","year":2008,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Uniprocessor system; Verilog; Discrete event simulation; Event (particle physics); Parallel computing; Overhead (engineering); Synchronization (alternating current); Embedded system; Multiprocessing; Simulation; Operating system; Field-programmable gate array","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":[0.001878414,0.001154768,0.000854835,0.0009821287,0.000607283,0.001228059,0.001898652,0.000589042,0.008176332],"category_scores_gemma":[0.006397699,0.0007766204,0.001303558,0.0007984271,0.0009318556,0.001372102,0.001943453,0.002042633,0.001696729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001439737,"about_ca_system_score_gemma":0.00137209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002696729,"about_ca_topic_score_gemma":0.003976024,"domain_scores_codex":[0.9984853,0.0004904158,0.00008950516,0.00021266,0.0005887442,0.0001335021],"domain_scores_gemma":[0.9962614,0.002513062,0.0002346356,0.0004957165,0.000429336,0.00006578826],"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":[0.0001144265,0.00006181069,0.0005727512,0.0001900179,0.00004822956,0.0001002892,0.0001014943,0.8318633,0.005285368,0.05372268,0.00201213,0.1059276],"study_design_scores_gemma":[0.00002172069,0.00001715425,0.00005063126,0.00001238748,0.00001021277,0.00001934861,0.00001154123,0.9737288,0.001813465,0.0218036,0.002505647,0.000005533272],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001665237,0.00007193064,0.9954842,0.00006187695,0.00001377163,0.00004020144,0.00003285044,0.0008327315,0.001797201],"genre_scores_gemma":[0.225702,0.0003479635,0.767004,0.0001200235,0.00005004363,0.0005687259,0.0003341268,0.001160477,0.004712727],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008176332,"threshold_uncertainty_score":0.02735251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0322092571060511,"score_gpt":0.2609372840446834,"score_spread":0.2287280269386323,"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."}}