{"id":"W7133087510","doi":"","title":"Impact of FPGA Architectures on Area and Performance of CGRA Overlays","year":2020,"lang":"","type":"dissertation","venue":"TSpace","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Field-programmable gate array; Leverage (statistics); Architecture; Overlay; Performance improvement","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004037186,0.0006999068,0.001244596,0.0005179155,0.00009734509,0.00008074621,0.001164208,0.0004141283,0.00004803713],"category_scores_gemma":[0.0001709688,0.0006169524,0.0004028045,0.0007666199,0.0001752692,0.0001400597,0.0001746123,0.0006782297,0.000007184448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001064974,"about_ca_system_score_gemma":0.0004544343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005406085,"about_ca_topic_score_gemma":0.00002429331,"domain_scores_codex":[0.9966395,0.0002516603,0.0008950665,0.0008989397,0.00086766,0.0004471726],"domain_scores_gemma":[0.9964537,0.000349966,0.001517802,0.001118414,0.0003302389,0.000229861],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01217714,0.001295368,0.0452227,0.0193509,0.002027526,0.0001082243,0.401578,0.005220796,0.3523727,0.007409937,0.004311359,0.1489253],"study_design_scores_gemma":[0.001242022,0.04059034,0.1704549,0.008184292,0.0002167734,0.00007239418,0.001432127,0.1513655,0.6235177,0.0008512867,0.00008759451,0.001985069],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831195,0.0007315477,0.008631492,0.00004901978,0.0002230804,0.0009216203,0.00001999544,0.0001300205,0.006173712],"genre_scores_gemma":[0.9949759,0.0002375279,0.004104842,0.00002200209,0.00006156058,0.00003024964,0.00002342115,0.00005287475,0.0004915734],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4001458,"threshold_uncertainty_score":0.9996282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02698740628452994,"score_gpt":0.3345761978167221,"score_spread":0.3075887915321922,"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."}}