{"id":"W4400081222","doi":"10.1145/3655038.3665953","title":"Breaking Barriers: Expanding GPU Memory with Sub-Two Digit Nanosecond Latency CXL Controller","year":2024,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science; Latency (audio); Nanosecond; CAS latency; Controller (irrigation); Computer hardware; Memory controller; Semiconductor memory; Physics; Telecommunications; Optics","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":[0.0002021056,0.0003832021,0.0002394927,0.0003822097,0.0003762472,0.0008209489,0.001812746,0.0003334174,0.004011211],"category_scores_gemma":[0.0006196845,0.0002019913,0.0001610251,0.0003435634,0.0003722409,0.001784817,0.001400024,0.0006416533,0.0009207188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008412576,"about_ca_system_score_gemma":0.0008117921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001780145,"about_ca_topic_score_gemma":0.002623309,"domain_scores_codex":[0.9998136,0.00001709078,0.0000108026,0.00003636436,0.00008044606,0.0000416194],"domain_scores_gemma":[0.9996433,0.00006448803,0.00005450522,0.0001046642,0.00009547817,0.00003763987],"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":[0.001129872,0.0003066051,0.00568204,0.0005782982,0.00006602562,0.001098675,0.0009968872,0.03487595,0.6030548,0.04730716,0.03296058,0.2719431],"study_design_scores_gemma":[0.0001747983,0.0008581849,0.001685762,0.00007778212,0.0000577632,0.0006867974,0.000323084,0.4456476,0.448733,0.009115797,0.09254043,0.00009894712],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4551061,0.003276072,0.4907291,0.001452061,0.0005256209,0.0002425859,0.0003926779,0.01515229,0.03312354],"genre_scores_gemma":[0.8639939,0.0003924403,0.1235177,0.0004873683,0.00006946624,0.0001323446,0.0002864877,0.0004293559,0.01069089],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004011211,"threshold_uncertainty_score":0.01341885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008883316011168568,"score_gpt":0.2487212482697577,"score_spread":0.2398379322585892,"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."}}