{"id":"W3158975875","doi":"10.1109/iscas51556.2021.9401197","title":"Acceleration of the Secure Hash Algorithm-256 (SHA-256) on an FPGA-CPU Cluster Using OpenCL","year":2021,"lang":"en","type":"article","venue":"","topic":"Cryptographic Implementations and Security","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; École de Technologie Supérieure","funders":"CMC Microsystems","keywords":"Computer science; Field-programmable gate array; Hash function; Cryptographic hash function; Implementation; Secure Hash Algorithm; Parallel computing; Throughput; Cryptography; Ranging; Embedded system; SHA-2; Algorithm; Operating system; Wireless; Programming language","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002808941,0.000666026,0.0002547943,0.0006639719,0.0002945387,0.0005412279,0.001168408,0.0002369269,0.00579425],"category_scores_gemma":[0.0008205496,0.0001723042,0.0001881225,0.0004912222,0.0002120343,0.0006420298,0.0003536381,0.0003735824,0.001043281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007419204,"about_ca_system_score_gemma":0.0007534361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001618965,"about_ca_topic_score_gemma":0.002342835,"domain_scores_codex":[0.9995704,0.00006545983,0.00002740806,0.000061125,0.0001494211,0.0001261578],"domain_scores_gemma":[0.9994773,0.0001317474,0.00006139223,0.0001107106,0.0001850227,0.00003385316],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004313303,0.0006419256,0.01017703,0.001208494,0.0001740037,0.001489527,0.0004797952,0.1649525,0.342427,0.01815014,0.01716976,0.4388165],"study_design_scores_gemma":[0.0004175968,0.002239423,0.004979247,0.00007307242,0.00009531422,0.0006308356,0.0001704748,0.470112,0.4957809,0.002480932,0.02292906,0.0000912089],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7657784,0.0008782668,0.1926573,0.0002154756,0.0001767603,0.0002225518,0.0003645933,0.01254805,0.02715864],"genre_scores_gemma":[0.9470125,0.0001159123,0.04785008,0.00004008755,0.00001310461,0.00007019902,0.0003722669,0.000233116,0.00429265],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00579425,"threshold_uncertainty_score":0.01938373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04708639446509078,"score_gpt":0.3250296744506166,"score_spread":0.2779432799855258,"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."}}