{"id":"W2046643070","doi":"10.4028/www.scientific.net/amr.1049-1050.2126","title":"Speculative High Performance Computation on Heterogeneous Multi-Core","year":2014,"lang":"en","type":"article","venue":"Advanced materials research","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Speculative multithreading; Computer science; Speedup; Parallel computing; Many core; Computation; Homogeneous; Benchmark (surveying); Thread (computing); Multi-core processor; Speculation; Computer architecture; Multithreading; Operating system; Algorithm","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":[0.0002420285,0.0003430296,0.0002915287,0.0002670715,0.0003867156,0.0004024032,0.0006991466,0.0001925171,0.0007738903],"category_scores_gemma":[0.0005902714,0.0001847058,0.000275738,0.0004622747,0.0004627513,0.0006947761,0.0003824426,0.0003018516,0.00007249003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005033485,"about_ca_system_score_gemma":0.0006925103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003326308,"about_ca_topic_score_gemma":0.003400951,"domain_scores_codex":[0.9998629,0.00003552444,0.000007095868,0.00002903429,0.00004208084,0.00002326359],"domain_scores_gemma":[0.9997154,0.00009244443,0.00003804147,0.00007584065,0.00005454934,0.00002371481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005769279,0.0001049492,0.006567354,0.0001776032,0.0001151697,0.000379481,0.0002080912,0.8198483,0.08498861,0.03178836,0.001555286,0.05368988],"study_design_scores_gemma":[0.00001294136,0.00004853689,0.0003574876,0.000001727624,0.00001102445,0.0000128672,0.00001083092,0.989777,0.00699226,0.002249636,0.0005217622,0.000003975148],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6383252,0.0009030395,0.3529647,0.0002293805,0.00007228544,0.00005487022,0.00009069574,0.00157437,0.00578537],"genre_scores_gemma":[0.9657626,0.0001703533,0.03321525,0.00002755464,0.000009597223,0.00002709435,0.00006972703,0.00003621906,0.0006816305],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003326308,"threshold_uncertainty_score":0.006613851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07708414911293841,"score_gpt":0.3795280697873424,"score_spread":0.302443920674404,"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."}}