{"id":"W4393576971","doi":"10.1145/3626202.3637557","title":"HiSpMV: Hybrid Row Distribution and Vector Buffering for Imbalanced SpMV Acceleration on FPGAs","year":2024,"lang":"en","type":"article","venue":"","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Field-programmable gate array; Acceleration; Computer science; Parallel computing; Distribution (mathematics); Embedded system; Mathematics; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001423114,0.00008826442,0.00008109752,0.00003396064,0.0001242971,0.0004182677,0.0001352572,0.000021299,0.000004499425],"category_scores_gemma":[0.00005985206,0.00007579049,0.00003398679,0.0001188749,0.000009660549,0.0003770374,0.00004028083,0.00006376203,0.00001277448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005748572,"about_ca_system_score_gemma":0.00002511064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001106568,"about_ca_topic_score_gemma":0.000003444589,"domain_scores_codex":[0.999299,0.00001055493,0.0001141745,0.0003051237,0.00009659143,0.0001745337],"domain_scores_gemma":[0.9996468,0.0001238014,0.0000184856,0.0001324157,0.00003143641,0.00004710317],"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":[0.000001114531,0.00003275498,0.0005265559,0.000124613,0.00001810566,0.00001881057,0.0001461361,0.0002607774,0.02208447,0.3318949,0.002966375,0.6419253],"study_design_scores_gemma":[0.0002216962,0.0001658459,0.005384115,0.000120296,0.000007475184,0.00003002881,0.000007555043,0.9515436,0.0324154,0.005192499,0.004691679,0.000219785],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08877195,0.0001079497,0.9085879,0.0009320664,0.0003624541,0.0001340345,0.00001047173,0.0003721944,0.0007210281],"genre_scores_gemma":[0.9985211,0.000006973712,0.0009435476,0.0001251131,0.0001677878,0.00001935745,0.00002933062,0.000006076199,0.0001806946],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9512829,"threshold_uncertainty_score":0.4033366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02127032867942789,"score_gpt":0.2535692154083808,"score_spread":0.232298886728953,"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."}}