{"id":"W7127301437","doi":"10.1109/icfpt67023.2025.00032","title":"Heuristic &amp; Expert-Guided Buffer Sizing for Neural Network Inference Applications on FPGAs","year":2025,"lang":"en","type":"article","venue":"","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"","keywords":"Sizing; Artificial neural network; Pipeline (software); Buffer (optical fiber); Heuristic; Throughput; Field-programmable gate array","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":[0.000346785,0.0001831941,0.0002212361,0.0001193938,0.0002256354,0.0002109529,0.001072281,0.0000907764,0.000008215432],"category_scores_gemma":[0.0001406333,0.0001624876,0.00008499486,0.0005284838,0.00003237638,0.0001876569,0.0002117599,0.0001192715,0.0000402411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007610895,"about_ca_system_score_gemma":0.00007494353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005406443,"about_ca_topic_score_gemma":0.000026637,"domain_scores_codex":[0.9984869,0.0000874426,0.0003787913,0.0005130536,0.0001715467,0.0003622319],"domain_scores_gemma":[0.9976985,0.0009243313,0.00008818168,0.001059746,0.0001606934,0.00006858856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000450364,0.00004511906,0.0001581438,0.00003716638,0.00001530665,7.040128e-7,0.000133485,0.001378648,0.001120612,0.8776485,0.1009557,0.0185021],"study_design_scores_gemma":[0.0006975577,0.000229653,0.0004554326,0.0003768243,0.00002103467,0.00001378675,0.00003024546,0.316596,0.01202044,0.3271062,0.3414581,0.0009946452],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002301117,0.0001979531,0.9803384,0.001114842,0.0002643429,0.001154132,0.000001229926,0.001052652,0.01564632],"genre_scores_gemma":[0.5994657,0.00001356723,0.3904601,0.003458753,0.0002171717,0.002049895,0.000005705683,0.00001594689,0.004313104],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5992356,"threshold_uncertainty_score":0.6626052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06359660156618083,"score_gpt":0.3668259358889053,"score_spread":0.3032293343227245,"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."}}