{"id":"W2145908511","doi":"10.1109/hpca.1995.386553","title":"How useful are non-blocking loads, stream buffers and speculative execution in multiple issue processors?","year":2002,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Blocking (statistics); Parallel computing; Cache; Compiler; Stream processing; Byte; Latency (audio); Embedded system; Operating system; Computer network","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":[0.0001092677,0.0001446317,0.000159479,0.0001656014,0.0001021335,0.0002590093,0.0002800064,0.00007079739,0.00000910906],"category_scores_gemma":[0.00006936197,0.0001330695,0.00002365998,0.0004088644,0.00003564557,0.0005117571,0.0001371795,0.0001140515,0.000006586433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004231112,"about_ca_system_score_gemma":0.000007556503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005516357,"about_ca_topic_score_gemma":0.00003491172,"domain_scores_codex":[0.9990364,0.00003962372,0.0001494804,0.0003916655,0.0001607835,0.0002220153],"domain_scores_gemma":[0.9994671,0.00005902807,0.0001041484,0.0002308041,0.00007720369,0.0000617152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000591056,0.001767662,0.6259921,0.0004657264,0.0001335003,0.0002585354,0.03448651,0.09397898,0.002902148,0.01216708,0.04429328,0.1834954],"study_design_scores_gemma":[0.0003707784,0.00004792694,0.01016653,0.00007270319,0.000001741306,0.000006382838,0.0001560392,0.981499,0.006473042,0.0003787317,0.0006165841,0.000210517],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09267664,0.0001563802,0.9023619,0.001796312,0.00005989918,0.0002598491,8.309102e-7,0.0004263132,0.002261823],"genre_scores_gemma":[0.9120113,0.00005791417,0.08691026,0.000129366,0.00003055449,0.000009837227,0.000001207159,0.000006655164,0.0008429315],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8875201,"threshold_uncertainty_score":0.5426416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02447792405124205,"score_gpt":0.2287553518277956,"score_spread":0.2042774277765536,"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."}}