{"id":"W2753694865","doi":"10.1109/mdat.2017.2748393","title":"Designing for FPGAs in the Cloud","year":2017,"lang":"en","type":"article","venue":"IEEE Design and Test","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Field-programmable gate array; Cloud computing; Computer science; Virtual machine; Flow (mathematics); Computer architecture; Embedded system; Distributed 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":[0.0007148015,0.00007968299,0.00008910302,0.00002441561,0.0003900127,0.000449475,0.0007400168,0.00003951723,6.643828e-7],"category_scores_gemma":[0.000267091,0.00005425401,0.00002464124,0.00005133613,0.00004275737,0.0001918583,0.0000372066,0.00007372865,0.000005070527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005449901,"about_ca_system_score_gemma":0.00002149726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002224425,"about_ca_topic_score_gemma":0.000007336811,"domain_scores_codex":[0.9993913,0.00004266493,0.00009215438,0.0001961011,0.00007958323,0.0001981625],"domain_scores_gemma":[0.9976944,0.001748755,0.00005892362,0.00044378,0.00002139174,0.00003275476],"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":[0.000110683,0.0006282346,0.07122319,0.000120863,0.00005967633,0.0003460647,0.01000718,0.003913482,0.005892305,0.1660964,0.1184218,0.6231802],"study_design_scores_gemma":[0.004749332,0.001317731,0.0852979,0.0003304206,0.00004497075,0.0001924037,0.0001173486,0.682856,0.01148236,0.1850678,0.02729314,0.001250639],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004420764,0.0001716394,0.9935557,0.0009429746,0.0003247882,0.0002704678,6.751047e-7,0.00004314523,0.0002697994],"genre_scores_gemma":[0.9280021,0.00002417554,0.07111436,0.0005446714,0.0001980382,0.00005167326,2.433007e-7,0.000005913952,0.0000587901],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9235814,"threshold_uncertainty_score":0.4334297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05926711564832351,"score_gpt":0.2773233507080989,"score_spread":0.2180562350597754,"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."}}