{"id":"W2156742168","doi":"10.1145/1133255.1133995","title":"Shared memory programming for large scale machines","year":2006,"lang":"en","type":"article","venue":"ACM SIGPLAN Notices","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Defense Advanced Research Projects Agency","keywords":"Computer science; Compiler; Parallel computing; Scalability; Runtime system; Distributed memory; Partitioned global address space; Optimizing compiler; Programming paradigm; Shared memory; Asynchronous communication; Programming language; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003038517,0.0001344237,0.0001484988,0.00009193389,0.0002326226,0.0002973919,0.001145434,0.00006016236,0.000006619784],"category_scores_gemma":[0.0001004309,0.0001212194,0.00006413255,0.0002055972,0.00001630287,0.0003549987,0.0002593284,0.00006644915,0.00001385814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001338203,"about_ca_system_score_gemma":0.00002271309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007072561,"about_ca_topic_score_gemma":0.00006824447,"domain_scores_codex":[0.9989443,0.00003449328,0.0002112688,0.0003425105,0.0001575303,0.0003098985],"domain_scores_gemma":[0.9989849,0.0002252624,0.0001214482,0.0005387689,0.0000843899,0.00004524892],"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":[0.0001703813,0.002332238,0.05903796,0.0009913475,0.0001858453,0.00008632223,0.006661803,0.05804057,0.00236835,0.1483219,0.2544597,0.4673436],"study_design_scores_gemma":[0.0009412487,0.0001755737,0.004394231,0.00006802235,0.00002092846,0.00001037342,0.00003990509,0.9400597,0.004225667,0.01153463,0.03794223,0.0005874585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009586799,0.0002539396,0.9854754,0.0008057432,0.0002205688,0.0003558628,0.00001531837,0.001191476,0.002094943],"genre_scores_gemma":[0.3277956,0.000001304735,0.6713005,0.0001868656,0.0001595967,0.00004118439,0.00004401911,0.00001065339,0.0004603205],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8820192,"threshold_uncertainty_score":0.4943184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01619749730491173,"score_gpt":0.2706697248421612,"score_spread":0.2544722275372495,"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."}}