import tempfile import time import pickle import pandas as pd from imc_utils.pps_e36311a import PPS_E36311A from imc_utils.build_config.cortex_m33 import BuildConfigM33 from imc_utils.build_config.test_env import TestEnv from imc_utils.serial_watch import SerialWatcher WORKSPACE_ROOT = "/home/ybkim/workspace/imc/imc_freertos_app_m33" NVM_RESET_BIN = f"{WORKSPACE_ROOT}/imc/utils/nvm_reset.elf" OPENOCD_SCRIPT = f"{WORKSPACE_ROOT}/imc_freertos_app_m33.cfg" def get_build_config(benchmark, config_name): config = get_default_build_config() config.bench_name = benchmark bench_repeat_count = config.bench_repeat_count_small[benchmark] config.bench_repeat_count = bench_repeat_count if config_name == "pass_count": config.use_checkpoint_pass_counter = True config.checkpoint_pass_count = config.pass_count_10ms[benchmark] if config_name == "adaptive": config.use_checkpoint_voltage_check = True config.split_loop = True config.enable_adaptive_loop_pass_count = True # config.enable_static_loop_pass_count = True # config.loop_pass_count = 50 config.max_loop_ids = 30 return config def main(): pps = PPS_E36311A() config = get_default_build_config() benchmarks = [ "vBasicMath", "vCrc", "vFFT", "vSha", "vStringSearch", "vMatMul", "vConv2d", "vAes", ] # benchmarks = [ # "vBasicMath" # ] configs = ["pass_count", "adaptive"] # configs = ["adaptive"] total_iterations = 20 for benchmark in benchmarks: for config_name in configs: all_records = [] config = get_build_config(benchmark, config_name) pps.set_voltage(3.3, 1) pps.set_current(0.1, 1) pps.output_on(1) env = TestEnv(WORKSPACE_ROOT, NVM_RESET_BIN, OPENOCD_SCRIPT) with tempfile.TemporaryDirectory() as build_dir: binary = env.build_binary(config, build_dir) env.clear_nvm_and_load_binary(binary, resume=False) pps.set_current(0.015, 1) time.sleep(1) env.resume_board(terminate=True) watcher = SerialWatcher(benchmark, total_iterations) records = watcher.run() for record in records: record.update( { # "loop_pass_count": loop_pass_count, } ) all_records.append(record) df = pd.DataFrame(all_records) columns = ["bench_name", "time_taken", "recovery", "stats", "is_correct"] print(df[columns]) save_records(benchmark, config_name, df) pps.output_off(1) def get_default_build_config(): config = BuildConfigM33() config.insert_compiler_checkpoints = True config.enable_extension = True config.use_checkpoint_pass_counter = False config.use_checkpoint_voltage_check = False config.bench_infinite_loop = True config.print_recovery_message = True config.split_loop = False config.enable_static_loop_pass_count = False config.enable_adaptive_loop_pass_count = False config.print_stats = True return config def save_records(bench_name, config_name, df): with open(f"output/{config_name}/{bench_name}.pickle", "wb") as f: pickle.dump(df, f) if __name__ == "__main__": main()