{"id":"W4229867184","doi":"10.1145/2714064.2660229","title":"Space-efficient multi-versioning for input-adaptive feedback-driven program optimizations","year":2014,"lang":"en","type":"article","venue":"ACM SIGPLAN Notices","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada)","funders":"U.S. Department of Energy; International Business Machines Corporation; National Science Foundation","keywords":"Executable; Computer science; Software versioning; Compiler; Heuristic; Code (set theory); Space (punctuation); Set (abstract data type); Function (biology); Programming language; Mathematical optimization; Algorithm; Software; Operating system; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0003172729,0.000200834,0.0002119324,0.0001744596,0.0004476457,0.0002851752,0.001343288,0.00009651677,0.000005134812],"category_scores_gemma":[0.0005251728,0.0001882769,0.00008747559,0.0003966814,0.0000649824,0.0002477104,0.0004426041,0.0001213016,0.00002617856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004080865,"about_ca_system_score_gemma":0.00005256539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002049916,"about_ca_topic_score_gemma":0.000006996861,"domain_scores_codex":[0.998543,0.0000996392,0.0002514591,0.0005046692,0.0002245964,0.0003766861],"domain_scores_gemma":[0.9981692,0.0005361727,0.0002157589,0.0007115853,0.0002398252,0.0001274825],"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":[0.00001177266,0.0002151535,0.0003648594,0.00001882006,0.00002390842,0.000001233783,0.0008173399,0.9664481,0.00003429194,0.01674598,0.001811401,0.01350718],"study_design_scores_gemma":[0.0005214781,0.0002697608,0.0004004568,0.00005059797,0.00001492622,0.000002166857,0.00004109049,0.9935185,0.0005720796,0.0002434621,0.004107212,0.000258249],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002532514,0.00003732949,0.9932847,0.0008482657,0.0002654929,0.0006562539,0.000005830918,0.001235526,0.001134106],"genre_scores_gemma":[0.3407855,0.000003997378,0.6587874,0.0001466554,0.00005810972,0.00006062077,0.00001590119,0.00001268325,0.0001291327],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.338253,"threshold_uncertainty_score":0.7677711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03233717448432247,"score_gpt":0.2904175895084425,"score_spread":0.25808041502412,"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."}}