{"id":"W2900224194","doi":"10.1109/mm.2018.2877288","title":"Accelerators and Coherence: An SoC Perspective","year":2018,"lang":"en","type":"article","venue":"IEEE Micro","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science Foundation of Sri Lanka; Defense Advanced Research Projects Agency; Ministère de l'Économie, de la Science et de l'Innovation - Québec; University of Illinois at Chicago; Politecnico di Torino","keywords":"Computer science; Computer architecture; Memory hierarchy; System on a chip; Embedded system; Coherence (philosophical gambling strategy); Variety (cybernetics); Perspective (graphical); Isolation (microbiology); Operating system","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001205261,0.0000814782,0.00007866169,0.00005735921,0.0001644726,0.0001777841,0.0003827389,0.00004539701,0.00001096676],"category_scores_gemma":[0.000009452903,0.00007669427,0.00001514334,0.0001690287,0.0001032055,0.0002706293,0.00007405868,0.00006670484,0.00002550646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002649519,"about_ca_system_score_gemma":0.00004078151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004955345,"about_ca_topic_score_gemma":0.000006830118,"domain_scores_codex":[0.9993729,0.00004097432,0.00008322031,0.0002865443,0.00007150968,0.0001448408],"domain_scores_gemma":[0.9994514,0.00001666915,0.00003915219,0.0002560855,0.0001731329,0.00006356221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007222391,0.0007982773,0.009901999,0.00004274143,0.0001636751,0.00006489951,0.07522523,0.000302909,0.4039009,0.1558738,0.1964698,0.1571835],"study_design_scores_gemma":[0.0007033188,0.0009684361,0.004225108,0.00004497307,0.000009721725,0.00008295295,0.0004001322,0.08094848,0.8761972,0.02726843,0.008305517,0.0008457705],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.217981,0.0001116528,0.7758849,0.0003056793,0.0002729637,0.00009499866,0.000001108337,0.0005215831,0.004826099],"genre_scores_gemma":[0.8428527,0.000009746828,0.1563275,0.0004464603,0.0001408382,0.000003126825,3.337195e-7,0.000005452497,0.0002138408],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6248717,"threshold_uncertainty_score":0.3127502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02276054028272846,"score_gpt":0.2967862888164338,"score_spread":0.2740257485337053,"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."}}