#!/usr/bin/env python3 """ Generate a driver/library benchmark based on DFA/PTA traces. Usage: PYTHONPATH=lib bin/generate-dfa-benchmark.py [options] [output.cc] generate-dfa-benchmarks reads in a DFA definition and generates runs (i.e., all words accepted by the DFA up to a configurable length). Each symbol corresponds to a function call. If arguments are specified in the DFA definition, each symbol corresponds to a function call with a specific set of arguments (so all argument combinations are present in the generated runs). Options: --depth= (default: 3) Maximum number of function calls per run --repeat= (default: 0) Repeat benchmark runs times. When 0, benchmark runs are repeated indefinitely and must be explicitly terminated with Ctrl+C / SIGINT --instance= Override the name of the class instance used for benchmarking --sleep= (default: 0) How long to sleep between function calls. """ import getopt import json import re import runner import sys import time import io import yaml from automata import PTA from harness import OnboardTimerHarness opt = dict() def benchmark_from_runs(pta: PTA, runs: list, harness: OnboardTimerHarness, benchmark_id: int = 0) -> io.StringIO: outbuf = io.StringIO() outbuf.write('#include "arch.h"\n') if 'includes' in pta.codegen: for include in pta.codegen['includes']: outbuf.write('#include "{}"\n'.format(include)) outbuf.write(harness.global_code()) outbuf.write('int main(void)\n') outbuf.write('{\n') for driver in ('arch', 'gpio', 'kout'): outbuf.write('{}.setup();\n'.format(driver)) if 'setup' in pta.codegen: for call in pta.codegen['setup']: outbuf.write(call) # There is a race condition between flashing the code and starting the UART log. # When starting the log before flashing, output from a previous benchmark may cause bogus data to be added. # When flashing first and then starting the log, the first log lines may be lost. # To work around this, we flash first, then start the log, and use this delay statement to ensure that no output is lost. # This is also useful to faciliate MIMOSA calibration after flashing. outbuf.write('arch.delay_ms(10000);\n') outbuf.write('while (1) {\n') outbuf.write(harness.start_benchmark()) class_prefix = '' if 'instance' in opt: class_prefix = '{}.'.format(opt['instance']) elif 'instance' in pta.codegen: class_prefix = '{}.'.format(pta.codegen['instance']) num_transitions = 0 num_traces = 0 for run in runs: outbuf.write(harness.start_run()) harness.start_trace() param = pta.get_initial_param_dict() for transition, arguments, parameter in run: num_transitions += 1 harness.append_transition(transition.name, param, arguments) harness.append_state(transition.destination.name, parameter) outbuf.write('// {} -> {}\n'.format(transition.origin.name, transition.destination.name)) if transition.is_interrupt: outbuf.write('// wait for {} interrupt\n'.format(transition.name)) transition_code = '// TODO add startTransition / stopTransition calls to interrupt routine' else: transition_code = '{}{}({});'.format(class_prefix, transition.name, ', '.join(map(str, arguments))) outbuf.write(harness.pass_transition(pta.get_transition_id(transition), transition_code, transition = transition)) param = parameter outbuf.write('// current parameters: {}\n'.format(', '.join(map(lambda kv: '{}={}'.format(*kv), param.items())))) if opt['sleep']: outbuf.write('arch.delay_ms({:d}); // {}\n'.format(opt['sleep'], transition.destination.name)) outbuf.write(harness.stop_run(num_traces)) outbuf.write('\n') num_traces += 1 outbuf.write(harness.stop_benchmark()) outbuf.write('}\n') outbuf.write('return 0;\n') outbuf.write('}\n') return outbuf def run_benchmark(application_file: str, pta: PTA, runs: list, arch: str, app: str, run_args: list, harness: object, sleep: int = 0, repeat: int = 0, run_offset: int = 0, runs_total: int = 0): outbuf = benchmark_from_runs(pta, runs, harness) with open(application_file, 'w') as f: f.write(outbuf.getvalue()) print('[MAKE] building benchmark with {:d} runs'.format(len(runs))) # assume an average of 10ms per transition. Mind the 10s start delay. run_timeout = 10 + num_transitions * (sleep+10) / 1000 if repeat: run_timeout *= repeat needs_split = False try: runner.build(arch, app, run_args) except RuntimeError: if len(runs) > 50: # Application is too large -> split up runs needs_split = True else: # Unknown error raise # This has been deliberately taken out of the except clause to avoid nested exception handlers # (they lead to pretty interesting tracebacks which are probably more confusing than helpful) if needs_split: print('[MAKE] benchmark code is too large, splitting up') mid = len(runs) // 2 results = run_benchmark(application_file, pta, runs[:mid], arch, app, run_args, harness, sleep, repeat, run_offset = run_offset, runs_total = runs_total) harness.reset() results.extend(run_benchmark(application_file, pta, runs[mid:], arch, app, run_args, harness, sleep, repeat, run_offset = run_offset + mid, runs_total = runs_total)) return results runner.flash(arch, app, run_args) monitor = runner.get_monitor(arch, callback = harness.parser_cb) if arch == 'posix': print('[RUN] Will run benchmark for {:.0f} seconds'.format(run_timeout)) lines = monitor.run(int(run_timeout)) return [(runs, harness, lines)] # TODO Benchmark bei zu vielen Transitionen in mehrere Programme # aufteilen und diese nacheinander bis zu X % completion (220%) # laufen lassen, zwischendurch jeweils automatisch neu bauen etc. try: slept = 0 while repeat == 0 or slept / run_timeout < 1: time.sleep(5) slept += 5 print('[RUN] {:d}/{:d} ({:.0f}%), current benchmark at {:.0f}%'.format(run_offset, runs_total, run_offset * 100 / runs_total, slept * 100 / run_timeout)) except KeyboardInterrupt: pass lines = monitor.get_lines() monitor.close() return [(runs, harness, lines)] if __name__ == '__main__': try: optspec = ( 'arch= ' 'app= ' 'depth= ' 'instance= ' 'repeat= ' 'run= ' 'sleep= ' 'timer-pin= ' 'trace-filter= ' ) raw_opts, args = getopt.getopt(sys.argv[1:], "", optspec.split(' ')) for option, parameter in raw_opts: optname = re.sub(r'^--', '', option) opt[optname] = parameter if 'depth' in opt: opt['depth'] = int(opt['depth']) else: opt['depth'] = 3 if 'repeat' in opt: opt['repeat'] = int(opt['repeat']) else: opt['repeat'] = 0 if 'sleep' in opt: opt['sleep'] = int(opt['sleep']) else: opt['sleep'] = 0 if 'trace-filter' in opt: trace_filter = [] for trace in opt['trace-filter'].split(): trace_filter.append(trace.split(',')) opt['trace-filter'] = trace_filter else: opt['trace-filter'] = None except getopt.GetoptError as err: print(err) sys.exit(2) modelfile = args[0] with open(modelfile, 'r') as f: if '.json' in modelfile: pta = PTA.from_json(json.load(f)) else: pta = PTA.from_yaml(yaml.safe_load(f)) if 'timer-pin' in opt: timer_pin = opt['timer-pin'] else: timer_pin = 'GPIO::p1_0' runs = list(pta.dfs(opt['depth'], with_arguments = True, with_parameters = True, trace_filter = opt['trace-filter'])) num_transitions = len(runs) if len(runs) == 0: print('DFS returned no traces -- perhaps your trace-filter is too restrictive?', file=sys.stderr) sys.exit(1) need_return_values = False if next(filter(lambda x: len(x.return_value_handlers), pta.transitions), None): need_return_values = True harness = OnboardTimerHarness(gpio_pin = timer_pin, pta = pta, counter_limits = runner.get_counter_limits_us(opt['arch']), log_return_values = need_return_values) if len(args) > 1: results = run_benchmark(args[1], pta, runs, opt['arch'], opt['app'], opt['run'].split(), harness, opt['sleep'], opt['repeat'], runs_total = len(runs)) json_out = { 'opt' : opt, 'pta' : pta.to_json(), 'traces' : harness.traces, 'raw_output' : list(map(lambda x: x[2], results)), } with open(time.strftime('ptalog-%Y%m%d-%H%M%S.json'), 'w') as f: json.dump(json_out, f) else: outbuf = benchmark_from_runs(pta, runs, harness) print(outbuf.getvalue()) sys.exit(0)