{"id":"W4406157368","doi":"10.1109/scw63240.2024.00065","title":"Design and Implementation of MPI-Native GPU-Initiated MPI Partitioned Communication","year":2024,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Parallel computing; Message passing; Message Passing Interface","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003915956,0.00006229755,0.00007533079,0.0001077707,0.00007503663,0.0001119486,0.0001986541,0.00002648799,0.00002780603],"category_scores_gemma":[0.00001215433,0.00005700813,0.0000145222,0.000364533,0.0000324628,0.000370976,0.00009910105,0.00004850666,0.000004473963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001765941,"about_ca_system_score_gemma":0.00005190082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004440468,"about_ca_topic_score_gemma":0.000003818694,"domain_scores_codex":[0.9993123,0.0001570598,0.0001943874,0.0001540535,0.0001025728,0.00007963901],"domain_scores_gemma":[0.9994035,0.0001818501,0.00005398524,0.0002019441,0.0001344358,0.00002421899],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001430269,0.0001113416,0.0004102419,0.0001138209,0.0001323807,0.00000577538,0.01283287,0.01247023,0.00264186,0.8256342,0.02010424,0.1255287],"study_design_scores_gemma":[0.0001764282,0.0001042392,0.00075406,0.00005059207,0.000007589016,0.000004833176,0.0001177951,0.9289373,0.04936673,0.02005706,0.0003108792,0.0001125405],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001592104,0.0002687905,0.9954156,0.0008115388,0.00003006843,0.0001790358,0.00000114555,0.0005010457,0.001200708],"genre_scores_gemma":[0.6670327,0.0001304929,0.3326913,0.00007419263,0.000003388966,0.00001480027,0.00001000092,0.00000314577,0.00004003798],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.916467,"threshold_uncertainty_score":0.2324724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05510419237434539,"score_gpt":0.3494644485519362,"score_spread":0.2943602561775908,"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."}}