{"id":"W4243315213","doi":"10.1109/dac.2018.8465799","title":"An Architecture-Agnostic Integer Linear Programming Approach to CGRA Mapping","year":2018,"lang":"en","type":"article","venue":"2018 55th ACM/ESDA/IEEE Design Automation Conference (DAC)","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Architecture; Computer architecture; Integer programming; Parallel computing; Integer (computer science); Set (abstract data type); Linear programming; Programming language; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007254425,0.000868491,0.0003955888,0.0004519853,0.0003589032,0.000946879,0.001106706,0.0005770084,0.003930293],"category_scores_gemma":[0.002041323,0.0003206934,0.0006292792,0.0004511149,0.0004834141,0.0009250093,0.001041553,0.001647069,0.0006669784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005085825,"about_ca_system_score_gemma":0.0009644057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001094559,"about_ca_topic_score_gemma":0.002334946,"domain_scores_codex":[0.9993703,0.0002170006,0.00002538101,0.00009450483,0.0002045921,0.00008827404],"domain_scores_gemma":[0.999324,0.0003769977,0.00005952105,0.00009658124,0.0001100995,0.00003282096],"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":[0.0001358119,0.0001722721,0.0006019039,0.0001653056,0.00003549823,0.0001522242,0.0001121958,0.7692646,0.01820235,0.04031157,0.003618235,0.167228],"study_design_scores_gemma":[0.00001305101,0.00003894688,0.00004245964,0.00000655568,0.000006381833,0.00002890414,0.00001512677,0.9848684,0.003007141,0.01012961,0.001838604,0.0000047496],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009800764,0.0001068299,0.9826849,0.0001569514,0.00003355565,0.00005306123,0.00004409843,0.001216266,0.005903631],"genre_scores_gemma":[0.2653014,0.0001375719,0.7299131,0.0002139355,0.00004322942,0.0001808503,0.0001945566,0.0004577019,0.003557682],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003930293,"threshold_uncertainty_score":0.01314819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09188084650747681,"score_gpt":0.3160060538151676,"score_spread":0.2241252073076908,"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."}}