{"id":"W4211002993","doi":"10.1145/3490422.3502328","title":"MAQO: A Scalable Many-Core Annealer for Quadratic Optimization on a Stratix 10 FPGA","year":2022,"lang":"en","type":"article","venue":"","topic":"Optimization and Packing Problems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Scalability; Field-programmable gate array; Parallel computing; Benchmark (surveying); Stratix; Solver; Block (permutation group theory); Optimization problem; Quadratic programming; Embedded system; Mathematical optimization; Algorithm; Mathematics","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":[0.0003350747,0.0008583259,0.0003777259,0.0003535924,0.0003135713,0.0005776241,0.001449034,0.0004023134,0.01423558],"category_scores_gemma":[0.000835364,0.0003112342,0.0004232425,0.0004357462,0.0002879081,0.000656686,0.000484283,0.0008624541,0.001964181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005364515,"about_ca_system_score_gemma":0.001018923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002942839,"about_ca_topic_score_gemma":0.006268993,"domain_scores_codex":[0.9997758,0.00004310981,0.0000122061,0.00004191221,0.00008151157,0.00004542456],"domain_scores_gemma":[0.9997832,0.00009656501,0.00002002417,0.00003733872,0.00003864286,0.00002426259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001881855,0.0004527704,0.003651347,0.001085703,0.0002557769,0.0006379867,0.0002587034,0.4027714,0.08648442,0.03288372,0.080236,0.3894003],"study_design_scores_gemma":[0.0004491663,0.0006313748,0.001211387,0.00004582225,0.00003500788,0.0001547714,0.00005689027,0.9237419,0.02682469,0.004347576,0.04245671,0.00004468371],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2691932,0.002643408,0.6125373,0.0006694883,0.0003778671,0.00066894,0.001655047,0.04375082,0.06850389],"genre_scores_gemma":[0.5952155,0.000420591,0.3843142,0.0003841704,0.00004649457,0.0003457654,0.002243646,0.0009994764,0.01603015],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01423558,"threshold_uncertainty_score":0.0476228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02676493419169152,"score_gpt":0.2359109737599167,"score_spread":0.2091460395682252,"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."}}