{"id":"W2166604263","doi":"10.1109/ipdps.2013.50","title":"Multi-threaded Graph Partitioning","year":2013,"lang":"en","type":"article","venue":"","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":152,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Economy, Trade and Industry; National Science Foundation","keywords":"Computer science; Parallel computing; Thread (computing); Speedup; Graph partition; Threading (protein sequence); Graph; Synchronization (alternating current); Multithreading; Theoretical computer science; Distributed computing; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002496999,0.00006006414,0.00005506292,0.00003990403,0.00002312043,0.00003037019,0.00004938633,0.00003862176,0.0008496076],"category_scores_gemma":[0.000003153703,0.00005314003,0.0000251904,0.00006636637,0.00001042212,0.0001378848,0.000005907272,0.00005263961,0.0004862584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007832078,"about_ca_system_score_gemma":0.000001139904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004383759,"about_ca_topic_score_gemma":0.000005814992,"domain_scores_codex":[0.999697,0.000003885198,0.00007898263,0.00005669855,0.00003821666,0.0001252014],"domain_scores_gemma":[0.9998406,0.000008271905,0.000004336293,0.00009317431,0.00001491488,0.00003869562],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[9.743923e-7,0.00008293591,0.006366633,0.0000896442,0.00008868612,0.000007597047,0.0005205144,0.001737573,0.6961716,0.006125583,0.2133995,0.07540882],"study_design_scores_gemma":[0.0006089725,0.00006520934,0.02886036,0.00005746777,0.00001714195,0.00001468774,0.0002175413,0.2073717,0.74027,0.01390317,0.007761291,0.00085244],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06797847,0.0002028924,0.8765237,0.00007105144,0.0001350853,0.0002854077,0.000001144215,0.004378212,0.05042403],"genre_scores_gemma":[0.9564337,0.00002376929,0.0428906,0.00006020254,0.00002194375,0.0000793596,0.000002496333,0.00001413044,0.0004737711],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8884553,"threshold_uncertainty_score":0.9302608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01698447838718365,"score_gpt":0.206530447974196,"score_spread":0.1895459695870123,"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."}}