{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003434746,0.0004453515,0.0002620819,0.0004516569,0.0001507477,0.0006574907,0.0008236784,0.0001879639,0.005558983],"category_scores_gemma":[0.0014133,0.0001980931,0.0001325097,0.0007264467,0.0003114868,0.0009622666,0.0005115082,0.000431258,0.0006717709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004446948,"about_ca_system_score_gemma":0.0004196489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001079099,"about_ca_topic_score_gemma":0.002203762,"domain_scores_codex":[0.9994692,0.00006995187,0.00005032163,0.00009880462,0.0002156221,0.0000961158],"domain_scores_gemma":[0.9987077,0.0003416167,0.0002932396,0.0003779773,0.0002062834,0.00007316811],"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":[0.003738113,0.0003868526,0.01313145,0.0009283555,0.0001244546,0.0006265438,0.0002032427,0.09600905,0.3811994,0.01699753,0.00750829,0.4791468],"study_design_scores_gemma":[0.0002600464,0.003978004,0.01923824,0.00009507589,0.0001638096,0.001283796,0.0002356032,0.3962431,0.5493836,0.004137123,0.02488308,0.00009859692],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8516008,0.0009461895,0.1236704,0.0001897158,0.0001609605,0.0001258414,0.0002217436,0.005391933,0.0176925],"genre_scores_gemma":[0.9358824,0.0002793314,0.05854103,0.0001127937,0.00003133306,0.00004775284,0.0001971552,0.0001724377,0.004735722],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005558983,"threshold_uncertainty_score":0.01859671,"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."}}