{"id":"W3133271864","doi":"10.1109/sc41405.2020.00057","title":"Compiler-Based Timing For Extremely Fine-Grain Preemptive Parallelism","year":2020,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"National Science Foundation","keywords":"Computer science; Parallel computing; Compiler; Timer; Heap (data structure); Control flow; Granularity; Optimizing compiler; Scheduling (production processes); Compile time; Operating system; Programming language","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":[0.0001782257,0.0001562871,0.0001878219,0.00005979504,0.0001420475,0.0001322497,0.0007799632,0.00005948465,0.00002528575],"category_scores_gemma":[0.0001013345,0.0001442706,0.0001057241,0.0002687794,0.00002796305,0.0001812933,0.0001421525,0.00009037576,0.00002388658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001758785,"about_ca_system_score_gemma":0.00006938964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006697248,"about_ca_topic_score_gemma":0.000002105086,"domain_scores_codex":[0.9988396,0.00005291598,0.0002432875,0.00043474,0.0001692683,0.0002602394],"domain_scores_gemma":[0.9991767,0.0001766913,0.0000946561,0.0002874573,0.00012833,0.0001361169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001640695,0.0003279051,0.0006488576,0.0001613441,0.00008869424,0.0000315606,0.003398222,0.1913743,0.001694987,0.2206775,0.4948077,0.08662481],"study_design_scores_gemma":[0.0004828627,0.0001852614,0.00006799339,0.00001344039,0.000003359311,0.000001035124,0.000006140966,0.9782498,0.004668026,0.001349182,0.01476803,0.0002048485],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001420928,0.00004589107,0.9858511,0.008561119,0.00007994578,0.0003721293,0.00000389574,0.001296772,0.003647025],"genre_scores_gemma":[0.2056042,0.000001586333,0.7898253,0.004127977,0.00007301691,0.00004269415,0.00001137149,0.00001109689,0.0003028095],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7868755,"threshold_uncertainty_score":0.5883185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07880913403745692,"score_gpt":0.2904329908552193,"score_spread":0.2116238568177624,"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."}}