{"id":"W4229606735","doi":"10.1109/micro.1994.717418","title":"Minimizing register requirements under resource-constrained rate-optimal software pipelining","year":2005,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Software pipelining; Computer science; Register allocation; Register (sociolinguistics); Parallel computing; Software; Resource (disambiguation); Computer architecture; Programming language; Computer network; Compiler","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":[0.0008325629,0.0004649315,0.0004881072,0.000292931,0.0002164152,0.0004358856,0.0006561874,0.0004377751,0.0007319438],"category_scores_gemma":[0.003301233,0.000317705,0.0002300268,0.0003865151,0.0005345013,0.001233681,0.0003853811,0.0003765838,0.0001484496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005219805,"about_ca_system_score_gemma":0.001074841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001205771,"about_ca_topic_score_gemma":0.001143132,"domain_scores_codex":[0.9995602,0.0001653194,0.00001910634,0.00006785165,0.0001101615,0.00007740711],"domain_scores_gemma":[0.9988239,0.0006865578,0.0001977718,0.0001266503,0.0001269298,0.00003817672],"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":[0.0001488065,0.00003411684,0.0003194192,0.00008976151,0.00001427909,0.00006175834,0.00005704098,0.9313023,0.02038908,0.02221736,0.0004121224,0.02495385],"study_design_scores_gemma":[0.00002452411,0.00007361497,0.0001306283,0.000004794077,0.000008752392,0.000021684,0.00001293791,0.9793793,0.005135381,0.01479295,0.000409463,0.000005989334],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2202286,0.000540213,0.7739704,0.0003496793,0.00001988846,0.00004669657,0.00007442546,0.0003375821,0.004432457],"genre_scores_gemma":[0.8789127,0.000367218,0.1189821,0.00004705785,0.00002667923,0.00006679123,0.00007477353,0.00008200682,0.001440687],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001205771,"threshold_uncertainty_score":0.004403055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03765351019215391,"score_gpt":0.2841889286662994,"score_spread":0.2465354184741455,"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."}}