{"id":"W2110659707","doi":"10.1109/pcee.2000.873615","title":"Parallel efficient implementation of hierarchical algorithms for module placement of large chips","year":2002,"lang":"en","type":"article","venue":"","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Computer science; Algorithm; Benchmark (surveying); Simulated annealing; Parallel computing; Convergence (economics); Electronic circuit; Placement; Multiprocessing; Integrated circuit; Physical design","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":[0.0004815228,0.0006181691,0.0006049722,0.0007502482,0.000492501,0.0007053232,0.001321242,0.0004744297,0.002473524],"category_scores_gemma":[0.001626405,0.0004127949,0.0005000095,0.0007940923,0.0003887571,0.0007614891,0.0008123813,0.0005671164,0.000605709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000767288,"about_ca_system_score_gemma":0.0009602513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002650938,"about_ca_topic_score_gemma":0.005379113,"domain_scores_codex":[0.999626,0.0001052917,0.00002914625,0.00006022352,0.0001292174,0.00005003521],"domain_scores_gemma":[0.9993851,0.0001979345,0.00006186426,0.0001922027,0.0001323667,0.00003050103],"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":[0.0002168231,0.00009921515,0.001409319,0.0002372919,0.00008182016,0.0001245764,0.0002224676,0.484965,0.0372625,0.02506932,0.003943455,0.4463681],"study_design_scores_gemma":[0.00003587566,0.0000747666,0.0003229663,0.000004793802,0.000009729373,0.00004392846,0.00002234656,0.9796276,0.01152921,0.005163455,0.003154764,0.00001058761],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01472311,0.00009371654,0.9822723,0.00003679739,0.00001950012,0.00004052541,0.00002782918,0.001494085,0.001292193],"genre_scores_gemma":[0.1493809,0.00006421695,0.848884,0.00002864247,0.00001292978,0.0001139535,0.0001307497,0.00008664327,0.001298034],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002650938,"threshold_uncertainty_score":0.008274794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0253424165269703,"score_gpt":0.2836081885869562,"score_spread":0.2582657720599859,"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."}}