{"id":"W3007153607","doi":"10.1145/3156685.3092256","title":"Analyzing memory management methods on integrated CPU-GPU systems","year":2017,"lang":"en","type":"article","venue":"ACM SIGPLAN Notices","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; CUDA; Central processing unit; Shared memory; Memory management; Multi-core processor; Parallel computing; Software; CPU shielding; Embedded system; Computer architecture; Operating system; 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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001004506,0.0001870011,0.0002356328,0.0002004179,0.0005723175,0.001098767,0.003434533,0.00007178786,0.00000593377],"category_scores_gemma":[0.0002387869,0.0001564612,0.00005801778,0.000151827,0.00004987492,0.0004167127,0.0007397866,0.0001640367,0.00005510676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004065317,"about_ca_system_score_gemma":0.00001830684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000162885,"about_ca_topic_score_gemma":0.000005438238,"domain_scores_codex":[0.9985477,0.0002362286,0.0002640875,0.0004648943,0.0002144374,0.0002726622],"domain_scores_gemma":[0.9970402,0.0002889672,0.0003430284,0.002163411,0.00007986875,0.00008448945],"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":[0.00005037923,0.000243301,0.002777861,0.0002887118,0.0004365024,0.0002623163,0.001284114,0.1022478,0.000356463,0.09924702,0.0198489,0.7729566],"study_design_scores_gemma":[0.0004994468,0.0001857661,0.005228484,0.0004024878,0.00005028843,0.00000991924,0.000125065,0.972878,0.003775283,0.002114868,0.01407603,0.0006543162],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002084388,0.0001879405,0.9637451,0.000598933,0.0008360737,0.0002069792,0.000001784334,0.0006859225,0.03165291],"genre_scores_gemma":[0.4454763,0.00003174511,0.5532168,0.0001272795,0.00006760502,0.00001416005,0.000004409103,0.00001036188,0.001051332],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8706302,"threshold_uncertainty_score":0.9999382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04683664990969114,"score_gpt":0.3514376544596579,"score_spread":0.3046010045499667,"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."}}