{"id":"W2053962247","doi":"10.1145/1508128.1508178","title":"Soft vector processors vs FPGA custom hardware","year":2009,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Datapath; Computer science; Field-programmable gate array; Scalability; Embedded system; Computer hardware; Pipeline (software); Parallel computing; Operating system","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":[0.0001318414,0.0001149834,0.0001215106,0.00008556731,0.0001169193,0.0001685543,0.0007620529,0.00005462947,0.00002616086],"category_scores_gemma":[0.00004140721,0.00009786385,0.00004483058,0.0003665108,0.00001395867,0.0003204363,0.00007899938,0.00009150832,0.0000833392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002193239,"about_ca_system_score_gemma":0.00005372566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005479116,"about_ca_topic_score_gemma":8.53131e-7,"domain_scores_codex":[0.9990971,0.00002495136,0.0001576275,0.0003041534,0.0001910106,0.0002251304],"domain_scores_gemma":[0.9993671,0.00002439315,0.00005489397,0.0003639412,0.0001105377,0.00007912298],"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":[0.00003257928,0.0005164237,0.0007169134,0.00004713276,0.00002993872,0.00005007187,0.002188146,0.02639838,0.0004434622,0.2031291,0.3238544,0.4425935],"study_design_scores_gemma":[0.0005109272,0.0005080501,0.005041454,0.00006492429,0.000006509862,0.00003621663,0.0000140001,0.8855442,0.02714707,0.01577522,0.06454813,0.0008032618],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004553891,0.00005498991,0.9745298,0.003115551,0.00008602131,0.00009529108,3.029508e-7,0.002073344,0.0195893],"genre_scores_gemma":[0.654173,0.00001050155,0.3395234,0.002428226,0.00005924195,0.000004919187,0.000001848516,0.000005592695,0.003793309],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8591458,"threshold_uncertainty_score":0.3990772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01366279720649041,"score_gpt":0.2559590641614218,"score_spread":0.2422962669549314,"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."}}