{"id":"W3120587606","doi":"10.1145/3429440","title":"Reducing Energy in GPGPUs through Approximate Trivial Bypassing","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Embedded Computing Systems","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Computer science; Register file; Parallel computing; General-purpose computing on graphics processing units; Exploit; Operand; Efficient energy use; Graphics processing unit; Energy consumption; Operating system; Graphics; Instruction set","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005735334,0.0003168546,0.0004762553,0.0003017726,0.0004404891,0.0005288909,0.001089699,0.0001841061,0.000005817948],"category_scores_gemma":[0.00007688814,0.0003469842,0.0001584804,0.001504258,0.00004738869,0.0004348635,0.00007257898,0.0004053997,0.000009660048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000261958,"about_ca_system_score_gemma":0.0002312362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004431244,"about_ca_topic_score_gemma":0.00001481136,"domain_scores_codex":[0.9967416,0.0005545647,0.0007888917,0.0009111718,0.0004273702,0.0005764108],"domain_scores_gemma":[0.9976307,0.0004387402,0.0002435727,0.001408669,0.0001817425,0.00009656281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001156374,0.0002782833,0.00001731032,0.00005678951,0.00004724104,0.00009467531,0.002719869,0.9433281,0.00083215,0.01092083,0.0002858014,0.04140732],"study_design_scores_gemma":[0.0007029066,0.00006499678,0.00001548466,0.0004730981,0.000009816446,0.0002087863,0.0002443426,0.9850732,0.01008024,0.001781919,0.0009204195,0.0004247752],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002957002,0.0003905865,0.9912012,0.0003480477,0.001651153,0.0001568116,0.000002775999,0.001096189,0.002196288],"genre_scores_gemma":[0.7401594,0.00003746867,0.2591517,0.0001937952,0.000114956,0.0000183537,0.00000690585,0.00002774925,0.0002896916],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7372024,"threshold_uncertainty_score":0.9998982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02612718248430757,"score_gpt":0.27582897298829,"score_spread":0.2497017905039824,"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."}}