{"id":"W2072076019","doi":"10.1145/1294313.1294319","title":"Custom code generation for soft processors","year":2007,"lang":"en","type":"article","venue":"ACM SIGARCH Computer Architecture News","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Compiler; Field-programmable gate array; Suite; Embedded system; Computer architecture; Personalization; Code (set theory); Software; Parallel computing; Operating system; Programming language","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":[0.0005001978,0.0007292409,0.0003182185,0.0008278148,0.0003339785,0.0007559785,0.001041899,0.0004065797,0.008769417],"category_scores_gemma":[0.003383838,0.0003940871,0.00051032,0.0008485363,0.000438013,0.000983574,0.001050998,0.0009778608,0.002471259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005331158,"about_ca_system_score_gemma":0.000974579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008853847,"about_ca_topic_score_gemma":0.002046824,"domain_scores_codex":[0.999243,0.0001196711,0.00007067639,0.0001233538,0.0003301682,0.0001131369],"domain_scores_gemma":[0.9974895,0.0007159294,0.0002998179,0.0009344232,0.0004899871,0.00007038026],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009897901,0.0002525887,0.007761853,0.000849989,0.000109996,0.0008497066,0.000460476,0.06615324,0.1521507,0.04579018,0.03903652,0.6855949],"study_design_scores_gemma":[0.0002368125,0.0004112628,0.00490554,0.0002256963,0.0001453253,0.001057265,0.0001836249,0.4320985,0.3784001,0.03389592,0.1483137,0.0001263295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1520327,0.0006567445,0.7703577,0.0004143094,0.0003471032,0.0004993489,0.001091487,0.04382689,0.03077366],"genre_scores_gemma":[0.5056794,0.0005225432,0.4592985,0.0007072795,0.0001133202,0.0004890858,0.003148484,0.008925988,0.02111532],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008769417,"threshold_uncertainty_score":0.02933663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02767314201053588,"score_gpt":0.2944678403683487,"score_spread":0.2667946983578128,"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."}}