{"id":"W7110212416","doi":"10.1145/3721462.3730950","title":"FreeRide: Harvesting Bubbles in Pipeline Parallelism","year":2025,"lang":"","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pipeline (software); Task (project management); Overhead (engineering); Parallelism (grammar); Graph; Data parallelism; Side effect (computer science); Resource (disambiguation)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009862473,0.001327964,0.000582732,0.0004510695,0.000584255,0.001242398,0.003038416,0.0008828638,0.01139109],"category_scores_gemma":[0.004532294,0.0008955708,0.000858298,0.0003957142,0.00104394,0.004118217,0.003357537,0.001994794,0.003588319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007596658,"about_ca_system_score_gemma":0.001501769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002964645,"about_ca_topic_score_gemma":0.004670397,"domain_scores_codex":[0.9994332,0.00009823948,0.00003743673,0.0001592593,0.0001555845,0.0001162023],"domain_scores_gemma":[0.9980252,0.0007078552,0.00007574796,0.0007170247,0.0002567697,0.0002174254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002136733,0.0007204489,0.01044646,0.001284422,0.0002823418,0.0008015624,0.002084479,0.1167552,0.1748241,0.03403369,0.1603232,0.4963073],"study_design_scores_gemma":[0.0003033579,0.000463174,0.001833666,0.00008084441,0.00005911827,0.0002440096,0.0002440736,0.7675527,0.118277,0.02687562,0.0839252,0.0001413203],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0720001,0.0008172097,0.7288712,0.0007691099,0.0004665591,0.0002621181,0.000784004,0.1843291,0.01170067],"genre_scores_gemma":[0.4857599,0.0003800851,0.4737717,0.0009832092,0.00009146889,0.000525756,0.003155513,0.02028086,0.01505138],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01139109,"threshold_uncertainty_score":0.03810692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01821108197293737,"score_gpt":0.2825840220147766,"score_spread":0.2643729400418393,"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."}}