{"url":"/dataset/leon3-sample-data","name":"GR712RC LEON3 Power Model Data","full_name":null,"description_markdown":"# Dataset Files\r\n\r\nThe official dataset files are hosted at [https://dx.doi.org/10.21227/1y7r-am78](https://dx.doi.org/10.21227/1y7r-am78). \r\n\r\n# Generating the models from the LEON3 sample data\r\n\r\nThe data for this paper is generated using a custom open-source methodology called **__REPPS__**. In order to replicate the results, first you must follow all the steps in [https://github.com/TSL-UOB/TP-REPPS](https://github.com/TSL-UOB/TP-REPPS) in order to install and configure all the scripts and supporting programs. Afterwards you can proceed with executing the following commands to generate the various models from the LEON3 data.\r\n\r\n**DISCLAIMER - If you have any issues please don't hesitate to contact via [email](mailto:kris.nikov@bris.ac.uk).**\r\n\r\n## Generate models trained on BEEBS and validated on the use_case_core application\r\n\r\n### ASIC Only Model\r\n```\r\n./octave_makemodel.sh -r /PATH/TO/ESL_paper_data/data/LEON3_BEEBS_finegrain.data -t /PATH/TO/ESL_paper_data/data/LEON3_use_case_finegrain.data -b /PATH/TO/ESL_paper_data/split/LEON3_BEEBS_use_case_split.data -p 6 -e 4 -d 2 -o 2 -s 20210421_leon3_beebs_ucc_pwr_fngr_nocyc_nocth_asicdata_avgrelerr_nfolds_ools.data\r\n```\r\n\r\n### Bottom-Up Search\r\n```\r\n./octave_makemodel.sh -r /PATH/TO/ESL_paper_data/data/LEON3_BEEBS_finegrain.data -t /PATH/TO/ESL_paper_data/data/LEON3_use_case_finegrain.data -b /PATH/TO/ESL_paper_data/split/LEON3_BEEBS_use_case_split.data -p 6 -l 9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24 -m 1 -n 16 -c 1 -g -i 50 -d 2 -o 2 -s 20210425_leon3_beebs_ucc_pwr_fngr_allev_nocyc_nocth_botup_avgrelerr_nfolds_ools.data\r\n```\r\n\r\n### Top-Down Search\r\n```\r\n./octave_makemodel.sh -r /PATH/TO/ESL_paper_data/data/LEON3_BEEBS_finegrain.data -t /PATH/TO/ESL_paper_data/data/LEON3_use_case_finegrain.data -b /PATH/TO/ESL_paper_data/split/LEON3_BEEBS_use_case_split.data -p 6 -l 9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24 -m 2 -n 1 -c 1 -g -i 50 -d 2 -o 2 -s 20210425_leon3_beebs_ucc_pwr_fngr_allev_nocyc_nocth_topdown_avgrelerr_nfolds_ools\r\n```\r\n\r\n## Validate the previous models on BEEBS as well (no need to redo all the event selection, just use same events)\r\n\r\n### ASIC Only Model\r\n```\r\n./octave_makemodel.sh -r /PATH/TO/ESL_paper_data/data/LEON3_BEEBS_finegrain.data -b /PATH/TO/ESL_paper_data/split/LEON3_BEEBS_BEEBS_split.data -p 6 -e 4 -d 2 -o 2 -s 20210421_leon3_beebs_beebs_pwr_fngr_nocyc_nocth_asicdata_avgrelerr_nfolds_ools.data\r\n```\r\n\r\n### Bottom-Up Search\r\n```\r\n./octave_makemodel.sh -r /PATH/TO/ESL_paper_data/data/LEON3_BEEBS_finegrain.data -b /PATH/TO/ESL_paper_data/split/LEON3_BEEBS_BEEBS_split.data -p 6 -e 24 -d 2 -o 2 -s 20210421_leon3_beebs_beebs_pwr_fngr_allev_nocyc_nocth_botup_avgrelerr_nfolds_ools.data\r\n```\r\n\r\n### Top-Down Search\r\n```\r\n./octave_makemodel.sh -r /PATH/TO/ESL_paper_data/data/LEON3_BEEBS_finegrain.data -b /PATH/TO/ESL_paper_data/split/LEON3_BEEBS_BEEBS_split.data -p 6 -e 9,10,12,13,14,15,16,18,19,20,22,23 -d 2 -o 2 -s 20210421_leon3_beebs_beebs_pwr_fngr_allev_nocyc_nocth_topdown_avgrelerr_nfolds_ools.data\r\n```\r\n\r\n# Visualise the data\r\n\r\n## Generate model per-sample breakdown files for the 1st run of the use_case_opt application\r\n\r\n### ASIC Only Model\r\n```\r\n./octave_makemodel.sh -r /PATH/TO/ESL_paper_data/data/LEON3_BEEBS_finegrain.data -t /PATH/TO/ESL_paper_data/data/LEON3_use_case_finegrain_1run.data -b /PATH/TO/ESL_paper_data/split/LEON3_BEEBS_onlyusecaseopt_split.data -p 6 -e 4 -d 2 -o 6 -s /PATH/TO/ESL_paper_data/20210421_leon3_beebs_uco_pwr_fngr_nocyc_nocth_asicdata_avgrelerr_nfolds_ools_1r.data\r\n```\r\n\r\n### Bottom-Up Search\r\n```\r\n./octave_makemodel.sh -r /PATH/TO/ESL_paper_data/data/LEON3_BEEBS_finegrain.data -t /PATH/TO/ESL_paper_data/data/LEON3_use_case_finegrain_1run.data -b /PATH/TO/ESL_paper_data/split/LEON3_BEEBS_onlyusecaseopt_split.data -p 6 -e 24 -d 2 -o 6 -s /PATH/TO/ESL_paper_data/20210427_leon3_beebs_uco_pwr_fngr_allev_nocyc_nocth_botup_avgrelerr_nfolds_ools_1r.data\r\n```\r\n\r\n### Top-Down Search\r\n```\r\n./octave_makemodel.sh -r /PATH/TO/ESL_paper_data/data/LEON3_BEEBS_finegrain.data -t /PATH/TO/ESL_paper_data/data/LEON3_use_case_finegrain_1run.data -b /PATH/TO/ESL_paper_data/split/LEON3_BEEBS_onlyusecaseopt_split.data -p 6 -e 9,10,12,13,14,15,16,18,19,20,22,23 -d 2 -o 6 -s /PATH/TO/ESL_paper_data/20210427_leon3_beebs_uco_pwr_fngr_allev_nocyc_nocth_topdown_avgrelerr_nfolds_ools_1r.data\r\n```\r\n\r\n## Generate model per-sample breakdown files for the 1st run of the BEEBS benchmarks\r\n\r\n### ASIC Only Model\r\n```\r\n./octave_makemodel.sh -r /PATH/TO/ESL_paper_data/data/LEON3_BEEBS_finegrain.data -t /PATH/TO/ESL_paper_data/data/LEON3_BEEBS_finegrain_1run.data -b /PATH/TO/ESL_paper_data/split/LEON3_BEEBS_BEEBS_split.data -p 6 -e 4 -d 2 -o 6 -s /PATH/TO/ESL_paper_data/20210423_leon3_beebs_beebs_pwr_fngr_nocyc_nocth_asicdata_avgrelerr_nfolds_ools_1r.data\r\n```\r\n\r\n### Bottom-Up Search\r\n```\r\n./octave_makemodel.sh -r /PATH/TO/ESL_paper_data/data/LEON3_BEEBS_finegrain.data -t /PATH/TO/ESL_paper_data/data/LEON3_BEEBS_finegrain_1run.data -b /PATH/TO/ESL_paper_data/split/LEON3_BEEBS_BEEBS_split.data -p 6 -e 24 -d 2 -o 6 -s /PATH/TO/ESL_paper_data/20210427_leon3_beebs_beebs_pwr_fngr_allev_nocyc_nocth_botup_avgrelerr_nfolds_ools_1r.data\r\n```\r\n\r\n### Top-Down Search\r\n```\r\n./octave_makemodel.sh -r /PATH/TO/ESL_paper_data/data/LEON3_BEEBS_finegrain.data -t /PATH/TO/ESL_paper_data/data/LEON3_BEEBS_finegrain_1run.data -b /PATH/TO/ESL_paper_data/split/LEON3_BEEBS_BEEBS_split.data -p 6 -e 9,10,12,13,14,15,16,18,19,20,22,23 -d 2 -o 6 -s /PATH/TO/ESL_paper_data/20210427_leon3_beebs_beebs_pwr_fngr_allev_nocyc_nocth_topdown_avgrelerr_nfolds_ools_1r.data\r\n```\r\n\r\n## Plot the model per-sample breakdwon data using `MODELDATA_plot.py`\r\n\r\n### Plot the use_case_opt 1st run per-sample physical measurements and model errors\r\n```\r\n./MODELDATA_plot.py -p 1 -x \"Samples[#]\" -t 10 -y \"Power[W]\" -b /PATH/TO/ESL_paper_data/data/LEON3_use_case_opt_finegrain_1run.data -l \"Sensor Data\" -i /PATH/TO/ESL_paper_data/20210421_leon3_beebs_uco_pwr_fngr_nocyc_nocth_asicdata_avgrelerr_nfolds_ools_1r.data -a 'ASIC Data Only' -i /PATH/TO/ESL_paper_data/20210427_leon3_beebs_uco_pwr_fngr_allev_nocyc_nocth_botup_avgrelerr_nfolds_ools_1r.data -a \"Bottom-Up Search\" -i /PATH/TO/ESL_paper_data/20210427_leon3_beebs_uco_pwr_fngr_allev_nocyc_nocth_topdown_avgrelerr_nfolds_ools_1r.data -a \"Top-Down Search\"\r\n```\r\n\r\n### Plot the BEEBS 1st run per-sample physical measurements and model errors\r\n```\r\n./MODELDATA_plot.py -p 1 -x \"Samples[#]\" -t 10 -y \"Power[W]\" -b /PATH/TO/ESL_paper_data/data/LEON3_BEEBS_finegrain_1run_physicaldata.data -l \"Sensor Data\" -i /PATH/TO/ESL_paper_data/20210423_leon3_beebs_beebs_pwr_fngr_nocyc_nocth_asicdata_avgrelerr_nfolds_ools_1r.data -a 'ASIC Data Only' -i /PATH/TO/ESL_paper_data/20210427_leon3_beebs_beebs_pwr_fngr_allev_nocyc_nocth_botup_avgrelerr_nfolds_ools_1r.data -a \"Bottom-Up Search\" -i /PATH/TO/ESL_paper_data/20210427_leon3_beebs_beebs_pwr_fngr_allev_nocyc_nocth_topdown_avgrelerr_nfolds_ools_1r.data -a \"Top-Down Search\"\r\n```","description_withheld":null,"homepage":"https://dx.doi.org/10.21227/1y7r-am78","introduced_date":"2021-05-26","introduced_date_note":null,"introduced_by":{"paper":"/paper/robust-and-accurate-fine-grain-power-models","title":"Robust and accurate fine-grain power models for embedded systems with no on-chip PMU","first_author":null,"url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["GR712RC LEON3 Power Model Data"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}