{"id":"W2269410433","doi":"10.1002/spe.2393","title":"Register allocation and spilling using the expected distance heuristic","year":2016,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Allocator; Register allocation; Computer science; Profiling (computer programming); Compiler; Parallel computing; Operating system","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":[0.001204633,0.0007724105,0.0009017788,0.001868399,0.0006714176,0.001279365,0.001246583,0.0006467834,0.002310018],"category_scores_gemma":[0.003891313,0.0004262107,0.0006925767,0.001488824,0.0006997245,0.001393891,0.0009576519,0.0007098114,0.0004871963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002083974,"about_ca_system_score_gemma":0.002829574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00544827,"about_ca_topic_score_gemma":0.007472047,"domain_scores_codex":[0.998689,0.0003643112,0.00009136637,0.0001994002,0.0004173488,0.0002385853],"domain_scores_gemma":[0.997941,0.0009878502,0.0003182028,0.0003245376,0.0003189001,0.0001094711],"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":[0.0004656153,0.0001604052,0.005265228,0.0001011357,0.00007467798,0.000137763,0.000113259,0.7685713,0.008747322,0.01092196,0.00318349,0.2022578],"study_design_scores_gemma":[0.00002167503,0.00005369249,0.0004259176,0.000008640095,0.00001597234,0.00003648991,0.00002151109,0.9913202,0.003975435,0.003357508,0.0007510756,0.00001177149],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3377222,0.00148692,0.6443861,0.0005550064,0.0001119778,0.0001303367,0.0002128551,0.006140628,0.009254051],"genre_scores_gemma":[0.7497641,0.0001722747,0.2470154,0.00009934236,0.00002808212,0.00005119572,0.0002436005,0.0003680482,0.002257897],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00544827,"threshold_uncertainty_score":0.01512033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02626437943403945,"score_gpt":0.3009378996028723,"score_spread":0.2746735201688328,"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."}}