{"id":"W7000453708","doi":"","title":"Fast Sparse Matrix Reordering on GPU for Cholesky Based Solvers","year":2024,"lang":"en","type":"other","venue":"eScholarship (California Digital Library)","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cholesky decomposition; Speedup; Implementation; Sparse matrix; Graph; Minimum degree algorithm; Reduction (mathematics); CUDA; Matrix (chemical analysis)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004728862,0.0009745308,0.0006304315,0.0005331051,0.0005535534,0.001026144,0.001257426,0.0005112742,0.01131176],"category_scores_gemma":[0.001933913,0.0003598831,0.0004882119,0.0009309283,0.0004362508,0.001187769,0.0009538625,0.001252997,0.003075853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007899032,"about_ca_system_score_gemma":0.001633884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007451472,"about_ca_topic_score_gemma":0.0160094,"domain_scores_codex":[0.9995481,0.00008020907,0.00002621114,0.00005688641,0.000236855,0.00005160584],"domain_scores_gemma":[0.9992566,0.000208282,0.0000474862,0.0001940335,0.0002479829,0.00004557162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007455323,0.0003400659,0.003987255,0.0005784617,0.0001194868,0.0005680507,0.0006414683,0.2341096,0.1478617,0.05063161,0.0458031,0.5146136],"study_design_scores_gemma":[0.00006418322,0.00007232552,0.0003105754,0.00002638341,0.000008334917,0.00006775519,0.00005589129,0.9525137,0.02858727,0.004298713,0.0139775,0.00001735894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03704554,0.000301042,0.939366,0.000311715,0.0001377623,0.0001297749,0.0003073431,0.01124946,0.01115134],"genre_scores_gemma":[0.1350103,0.000258307,0.8566103,0.0001060408,0.0000267656,0.0001326359,0.0009727965,0.0008891224,0.00599378],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01131176,"threshold_uncertainty_score":0.03784162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01606751837522267,"score_gpt":0.2431890435201492,"score_spread":0.2271215251449265,"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."}}