{"id":"W4416004258","doi":"10.1145/3731599.3767392","title":"Accelerating Intra-Node GPU Communication: A Performance Model for Multi-Path Transfers","year":2025,"lang":"","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Pipeline (software); Overhead (engineering); Key (lock); Path (computing); Models of communication; Communications system; Reliability (semiconductor)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005134894,0.000923635,0.0006629416,0.0006527098,0.0007725389,0.0009524721,0.002784712,0.001469921,0.002864069],"category_scores_gemma":[0.002634238,0.0004199084,0.0004919654,0.0007122277,0.0009119136,0.002532339,0.0008495625,0.001509832,0.0009916864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001728015,"about_ca_system_score_gemma":0.001314785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00669081,"about_ca_topic_score_gemma":0.004515523,"domain_scores_codex":[0.9995316,0.0001035925,0.00001188511,0.00008362364,0.0001780877,0.00009113995],"domain_scores_gemma":[0.9992786,0.0002964332,0.00008892854,0.0001066184,0.0001726674,0.00005674462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002923206,0.00003852844,0.0004153021,0.00002491406,0.000006946569,0.00004433155,0.00005068305,0.9764703,0.002955794,0.01448558,0.001283303,0.004195038],"study_design_scores_gemma":[0.00000198663,0.000009330156,0.00005363541,0.000001788057,0.000001461458,0.000008261064,0.000005547231,0.9974184,0.0003483985,0.00176018,0.0003880918,0.000002890888],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08504849,0.0006768011,0.8884917,0.00144077,0.0001584258,0.0001437069,0.0002411983,0.001564899,0.02223397],"genre_scores_gemma":[0.9117855,0.0009080049,0.07302172,0.0003023791,0.0001063402,0.0003871541,0.0002546579,0.0008413722,0.01239294],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00669081,"threshold_uncertainty_score":0.0133037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07152579302323961,"score_gpt":0.318105012464722,"score_spread":0.2465792194414824,"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."}}