{"id":"W4255023136","doi":"10.32920/ryerson.14647368","title":"Parallel Implementation of Non-slicing Floorplans with MPI and OpenMP","year":2021,"lang":"en","type":"preprint","venue":"","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Parallel computing; Computer science; Floorplan; Benchmark (surveying); Multiprocessing; Very-large-scale integration; Slicing; Computation; Computer architecture; Embedded system; Algorithm","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":[0.0000791088,0.0001600982,0.000253681,0.00007031418,0.00001471302,0.00004788336,0.00008830964,0.0001068755,0.0001208965],"category_scores_gemma":[8.769269e-7,0.0001399922,0.00002834615,0.00004794261,0.00001326453,0.00006506019,0.0001102223,0.0001730516,7.326673e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000216085,"about_ca_system_score_gemma":0.00002905733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006824582,"about_ca_topic_score_gemma":0.0004358427,"domain_scores_codex":[0.9994,0.000009562243,0.0002034249,0.0001725106,0.00009529402,0.0001191699],"domain_scores_gemma":[0.9996751,0.00001244777,0.0000395551,0.0002030185,0.00003641943,0.00003346789],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001049391,0.0002105228,0.1137312,0.01750623,0.003781348,0.0002956193,0.02986815,0.125764,0.3144097,0.002489909,0.02326562,0.3685727],"study_design_scores_gemma":[0.002340202,0.000432814,0.07239871,0.002003509,0.0004180039,0.0000860083,0.009842928,0.07170837,0.8372565,0.0006634175,0.000607068,0.002242496],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4028732,0.0002232322,0.590054,0.0000224772,0.00006196644,0.0004389082,0.0000201716,0.0002618577,0.006044196],"genre_scores_gemma":[0.936236,0.0003815775,0.06312427,0.00001870304,0.00002440057,0.00005644018,0.00008181323,0.00002914778,0.00004770492],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5333627,"threshold_uncertainty_score":0.5708715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01070693093958907,"score_gpt":0.259707047487965,"score_spread":0.2490001165483759,"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."}}