{"id":"W2106247612","doi":"10.1109/iscas.2005.1465387","title":"Application Specific Instruction-Set Processor Generation for Video Processing Based on Loop Optimization","year":2005,"lang":"en","type":"article","venue":"","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Instruction set; Application-specific instruction-set processor; Speedup; Computer architecture; Design space exploration; Embedded system; Hardware acceleration; Code generation; Profiling (computer programming); Integrated circuit design; Computer engineering; Parallel computing; Field-programmable gate array; Programming language; Operating system","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":[0.0003919045,0.000152572,0.0001266937,0.000204943,0.0002049297,0.0002910262,0.0003893553,0.00008649941,0.00000892675],"category_scores_gemma":[0.00002846242,0.0001436067,0.00003923688,0.0004587931,0.00001750663,0.001283096,0.0000198844,0.00006474511,0.00001669803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001616928,"about_ca_system_score_gemma":0.000094881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003081717,"about_ca_topic_score_gemma":0.000005013175,"domain_scores_codex":[0.9986111,0.00004146294,0.0003531319,0.0005285774,0.0002828377,0.0001829107],"domain_scores_gemma":[0.9989128,0.00003873359,0.00021529,0.0004574253,0.0003252249,0.00005050848],"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":[0.00002707102,0.0001459016,0.00004959723,0.0001215155,0.000004698575,2.801287e-7,0.00024386,0.5374333,0.02138945,0.03697646,0.006758327,0.3968495],"study_design_scores_gemma":[0.000311253,0.00007204829,0.000004999063,0.00002215048,0.000002154422,0.000003801777,0.000006201258,0.9096943,0.08496502,0.0003232475,0.00443393,0.0001609488],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003720525,0.00003068422,0.99558,0.0007686259,0.00008300639,0.001185569,0.000001786132,0.0008004864,0.001177787],"genre_scores_gemma":[0.3615774,0.000001987572,0.6369294,0.0004502923,0.0003114409,0.0005763503,0.00002974256,0.00001549219,0.0001079056],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3966886,"threshold_uncertainty_score":0.5856112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03282614773174092,"score_gpt":0.2756057481207733,"score_spread":0.2427796003890323,"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."}}