{"id":"W2264859574","doi":"10.1145/2856400.2876011","title":"A framework to transform in-core GPU algorithms to out-of-core algorithms","year":2016,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"","keywords":"Computer science; Porting; Out-of-core algorithm; Parallel computing; Core (optical fiber); Algorithm; Set (abstract data type); Many core; Multi-core processor; General-purpose computing on graphics processing units; Instruction set; Operating system; Programming language; Software; Graphics","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":[0.0006792267,0.001002941,0.0007232295,0.0009017418,0.0005897875,0.001300586,0.002308844,0.0009399094,0.005777874],"category_scores_gemma":[0.002176987,0.0004887184,0.001112715,0.000638882,0.0007602778,0.001360656,0.001730835,0.00231604,0.002394909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008121983,"about_ca_system_score_gemma":0.001421049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003502159,"about_ca_topic_score_gemma":0.004596529,"domain_scores_codex":[0.9993972,0.00010214,0.00004205249,0.00008299415,0.0002853748,0.00009034191],"domain_scores_gemma":[0.9993488,0.0001031742,0.00004103333,0.000191306,0.0002598102,0.00005591619],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001799132,0.0004508642,0.0009503813,0.0004256522,0.0001109259,0.0003991413,0.0003803086,0.1805189,0.04738575,0.2795289,0.02058673,0.4690826],"study_design_scores_gemma":[0.00005560117,0.0001544595,0.0002597854,0.00004668747,0.00003134003,0.0003564907,0.00004483254,0.8423101,0.02370296,0.08103517,0.05196449,0.00003817989],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009774821,0.00006096784,0.9957908,0.00005397435,0.00005088785,0.00004111787,0.00002126563,0.00146038,0.001543215],"genre_scores_gemma":[0.03943972,0.000169686,0.9558803,0.0001395358,0.0000642741,0.0001638291,0.0001351564,0.0007359493,0.003271529],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005777874,"threshold_uncertainty_score":0.01932889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04177681863237576,"score_gpt":0.3151536560112425,"score_spread":0.2733768373788667,"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."}}