{"id":"W2145230043","doi":"10.1145/2236584.2236586","title":"Reducing OLTP instruction misses with thread migration","year":2012,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Division of Information and Intelligent Systems; Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Online transaction processing; Computer science; Cache; Transactional memory; Thread (computing); Serialization; Database transaction; Transaction processing; Parallel computing; Embedded system; Operating system; Database","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005931708,0.0007131712,0.0004930174,0.0006357402,0.0004651778,0.0006635756,0.001306043,0.0003893939,0.001135566],"category_scores_gemma":[0.002964634,0.0002326376,0.0003101093,0.0009557014,0.0002397019,0.000813076,0.0008885823,0.0005899725,0.0005313564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000376403,"about_ca_system_score_gemma":0.000969346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001635851,"about_ca_topic_score_gemma":0.001859838,"domain_scores_codex":[0.9993216,0.000110806,0.00006767759,0.00009848741,0.0002497511,0.0001517981],"domain_scores_gemma":[0.9979722,0.000427672,0.0004426813,0.0005333846,0.0005131511,0.0001109128],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001176731,0.0007673643,0.0182226,0.000261825,0.000087035,0.0002917347,0.0004369303,0.08657103,0.2488357,0.003365808,0.006540103,0.6334432],"study_design_scores_gemma":[0.0002017845,0.001834422,0.01366275,0.00004909428,0.0001176676,0.0007112774,0.0003957812,0.7220056,0.2430583,0.004917537,0.01296804,0.00007773554],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7749364,0.001553652,0.2070646,0.0005429835,0.0001853251,0.0001826457,0.0001270337,0.007751684,0.00765571],"genre_scores_gemma":[0.9062874,0.0003196045,0.0906541,0.0001218,0.00005883464,0.00009344354,0.0001795272,0.0001822066,0.002103074],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001635851,"threshold_uncertainty_score":0.003798842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01813186774372141,"score_gpt":0.2509104091992491,"score_spread":0.2327785414555277,"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."}}