{"id":"W4416649506","doi":"10.1145/3768985","title":"Harmonics: Scalable Collective Scheduling in Multi-Tenant GPU Clusters","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ACM on Networking","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Huawei Technologies (Canada)","funders":"","keywords":"Scalability; Scheduling (production processes); Fair-share scheduling; Dynamic priority scheduling; Two-level scheduling; Cloud computing; Latency (audio); Fixed-priority pre-emptive scheduling","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":[0.001293505,0.0007241999,0.000646899,0.0003568502,0.001048917,0.001007719,0.002251759,0.0004707203,0.002687074],"category_scores_gemma":[0.00266006,0.0003695195,0.0003776774,0.0005584331,0.0007266246,0.001120507,0.001584035,0.0009657301,0.0005820603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00129482,"about_ca_system_score_gemma":0.00212209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01137126,"about_ca_topic_score_gemma":0.01593687,"domain_scores_codex":[0.9992513,0.0001919769,0.00003015884,0.0001545196,0.0001780916,0.0001940033],"domain_scores_gemma":[0.9988212,0.0002874862,0.0000767554,0.00034927,0.0001965277,0.0002686564],"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":[0.00134597,0.0003339718,0.005511646,0.0001724917,0.0001401071,0.000258852,0.00040367,0.8009554,0.02199202,0.01547472,0.03489032,0.1185208],"study_design_scores_gemma":[0.00008369362,0.00008365723,0.0004279655,0.000003572489,0.000008942246,0.00001586284,0.00005173059,0.990108,0.002821965,0.003278052,0.003105153,0.000011408],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3737008,0.001250392,0.5733015,0.001148921,0.0007070162,0.0004035532,0.000679168,0.03224352,0.01656521],"genre_scores_gemma":[0.851401,0.0001813796,0.1433932,0.0001818788,0.0000767762,0.0001833684,0.000719811,0.0008466424,0.003016072],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01137126,"threshold_uncertainty_score":0.02261013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04228128546511942,"score_gpt":0.2621340072771946,"score_spread":0.2198527218120752,"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."}}