{"id":"W2624632852","doi":"10.1145/3092255.3092256","title":"Analyzing memory management methods on integrated CPU-GPU systems","year":2017,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Astellas Pharma US","keywords":"Computer science; CUDA; Central processing unit; Memory management; Shared memory; Multi-core processor; Parallel computing; CPU shielding; Software; Uniform memory access; General-purpose computing on graphics processing units; Computer architecture; Embedded system; Operating system; Graphics; Overlay","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":[0.0009401158,0.0001324223,0.0001690686,0.0001697945,0.0004442519,0.0008346541,0.001613006,0.00004846741,0.000008033681],"category_scores_gemma":[0.00003705155,0.0001046663,0.00005461296,0.0001358695,0.00003024941,0.0002607042,0.0004180264,0.0001084517,0.00004187357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004531836,"about_ca_system_score_gemma":0.00001391186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001106197,"about_ca_topic_score_gemma":0.000001541499,"domain_scores_codex":[0.9989074,0.0001663396,0.0002091723,0.0003670245,0.0001498607,0.0002002043],"domain_scores_gemma":[0.9983066,0.00005683004,0.0001674948,0.001325926,0.00007726042,0.00006591568],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007312935,0.00008780746,0.0002134344,0.00004567379,0.0001111546,0.00004340138,0.0001633351,0.02985271,0.0001041231,0.3668561,0.01768349,0.5848315],"study_design_scores_gemma":[0.0001650324,0.00004712208,0.0005686881,0.00007954635,0.000006637328,0.000004073449,0.00002414947,0.9885665,0.002251126,0.0009921032,0.007088437,0.0002065675],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0000893254,0.00004600308,0.8395635,0.0003022338,0.000421082,0.0001333202,1.963908e-7,0.0007154732,0.1587288],"genre_scores_gemma":[0.1496749,0.00002821289,0.8417295,0.0001407531,0.00003268784,0.00001474857,0.00000111899,0.000007471162,0.008370629],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9587138,"threshold_uncertainty_score":0.8048589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03952331237887621,"score_gpt":0.3524734375098484,"score_spread":0.3129501251309723,"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."}}