' + title + '

#!/usr/bin/env python3 import argparse import os import sys from kernelNanoBench import * from tools.CPUID.cpuid import CPUID, micro_arch def writeHtmlFile(filename, title, head, body, includeDOCTYPE=True): with open(filename, 'w') as f: if includeDOCTYPE: f.write('\n') f.write('\n' '\n' '' '' + title + '\n' + head + '\n' '\n' + body + '\n' '\n') def main(): parser = argparse.ArgumentParser(description='Cycle-by-Cycle Measurements') parser.add_argument('-html', help='HTML filename [Default: graph.html]', nargs='?', const='', metavar='filename') parser.add_argument('-csv', help='CSV filename [Default: stdout]', nargs='?', const='', metavar='filename') parser.add_argument('-end_to_end', action='store_true', help='Do not try to remove overhead.') parser.add_argument('-asm', metavar='code', help='Assembler code string (in Intel syntax) to be benchmarked.') parser.add_argument('-asm_init', metavar='code', help='Assembler code string (in Intel syntax) to be executed once in the beginning.') parser.add_argument('-asm_late_init', metavar='code', help='Assembler code string (in Intel syntax) to be executed once immediately before the code to be benchmarked.') parser.add_argument('-asm_one_time_init', metavar='code', help='Assembler code string (in Intel syntax) to be executed once before the first measurement.') parser.add_argument('-code', metavar='filename', help='Binary file containing the code to be benchmarked.') parser.add_argument('-code_init', metavar='filename', help='Binary file containing code to be executed once in the beginning.') parser.add_argument('-code_late_init', metavar='filename', help='Binary file containing code to be executed once immediately before the code to be benchmarked.') parser.add_argument('-code_one_time_init', metavar='filename', help='Binary file containing code to be executed once before the first measurement.') parser.add_argument('-cpu', metavar='n', help='Pins the measurement thread to CPU n.') parser.add_argument('-config', metavar='filename', help='File with performance counter event specifications.', required=True) parser.add_argument('-unroll_count', metavar='n', help='Number of copies of the benchmark code inside the inner loop.', default=1) parser.add_argument('-loop_count', metavar='n', help='Number of iterations of the inner loop.') parser.add_argument('-n_measurements', metavar='n', help='Number of times the measurements are repeated.') parser.add_argument('-warm_up_count', metavar='n', help='Number of runs before the first measurement gets recorded.') parser.add_argument('-initial_warm_up_count', metavar='n', help='Number of runs before any measurement is performed.') parser.add_argument('-alignment_offset', metavar='n', help='Alignment offset.') parser.add_argument('-avg', action='store_const', const='avg', help='Selects the arithmetic mean (excluding the top and bottom 20%% of the values) as the ' 'aggregate function.') parser.add_argument('-median', action='store_const', const='med', help='Selects the median as the aggregate function.') parser.add_argument('-min', action='store_const', const='min', help='Selects the minimum as the aggregate function.') parser.add_argument('-max', action='store_const', const='max', help='Selects the maximum as the aggregate function.') parser.add_argument('-range', action='store_true', help='Outputs the range of the measured values (i.e., the minimum and the maximum).') parser.add_argument('-no_mem', action='store_true', help='The code for reading the perf. ctrs. does not make memory accesses.') parser.add_argument('-remove_empty_events', action='store_true', help='Removes events from the output that did not occur.') parser.add_argument('-verbose', action='store_true', help='Outputs the results of all performance counter readings.') args = parser.parse_args() uArch = micro_arch(CPUID()) detP23 = (uArch in ['SNB', 'IVB', 'HSW', 'BDW', 'SKL', 'SKX', 'CLX', 'KBL', 'CFL', 'CNL']) setNanoBenchParameters(basicMode=True, drainFrontend=True) setNanoBenchParameters(config=readFile(args.config), unrollCount=args.unroll_count, loopCount=args.loop_count, nMeasurements=args.n_measurements, warmUpCount=args.warm_up_count, initialWarmUpCount=args.initial_warm_up_count, alignmentOffset=args.alignment_offset, aggregateFunction=(args.avg or args.median or args.min or args.max or 'med'), range=args.range, noMem=args.no_mem, verbose=args.verbose, endToEnd=args.end_to_end) nbDict = runNanoBenchCycleByCycle(code=args.asm, codeBinFile=args.code, init=args.asm_init, initBinFile=args.code_init, lateInit=args.asm_late_init, lateInitBinFile=args.code_late_init, oneTimeInit=args.asm_one_time_init, oneTimeInitBinFile=args.code_one_time_init, cpu=args.cpu, detP23=detP23) if nbDict is None: print('Error: nanoBench did not return a valid result.', file=sys.stderr) if not args.end_to_end: print('Try using the -end_to_end option.', file=sys.stderr) exit(1) if (uArch in ['TGL', 'RKL']) and (not args.end_to_end): # on TGL and RKL, the wrmsr instruction sometimes appears to need an extra cycle print('Note: If the results look incorrect, try using the -end_to_end option.', file=sys.stderr) if args.remove_empty_events: for k in list(nbDict.keys()): if max(nbDict[k][0]) == 0: del nbDict[k] if args.csv is not None: if args.range: csvString = '\n'.join(k + ',' + ','.join(map(str, sum(zip(v, vMin, vMax), ()))) for k, (v, vMin, vMax) in nbDict.items()) else: csvString = '\n'.join(k + ',' + ','.join(map(str, v)) for k, (v, _, _) in nbDict.items()) if args.csv: with open(args.csv, 'w') as f: f.write(csvString + '\n') os.chown(args.csv, int(os.environ['SUDO_UID']), int(os.environ['SUDO_GID'])) else: print(csvString) if (args.html is not None) or (args.csv is None): from plotly.offline import plot import plotly.graph_objects as go fig = go.Figure() fig.update_xaxes(title_text='Cycle') for name, (values, minValues, maxValues) in nbDict.items(): e = None if args.range: array = [(m-v) for (v, m) in zip(values, maxValues)] arrayminus = [(v-m) for (v, m) in zip(values, minValues)] e = dict(type='data', symmetric=False, array=array, arrayminus=arrayminus) fig.add_trace(go.Scatter(y=values, error_y=e, mode='lines+markers', line_shape='linear', name=name, marker_size=5, hoverlabel = dict(namelength = -1))) config = {'displayModeBar': True, 'modeBarButtonsToRemove': ['autoScale2d', 'select2d', 'lasso2d'], 'modeBarButtonsToAdd': ['toggleSpikelines', 'hoverclosest', 'hovercompare', {'name': 'Toggle interpolation mode', 'icon': 'iconJS', 'click': 'interpolationJS'}]} body = plot(fig, include_plotlyjs='cdn', output_type='div', config=config) body = body.replace('"iconJS"', 'Plotly.Icons.drawline') body = body.replace('"interpolationJS"', 'function (gd) {Plotly.restyle(gd, "line.shape", gd.data[0].line.shape == "hv" ? "linear" : "hv")}') cmdLine = ' '.join(('"'+p+'"' if ((' ' in p) or (';' in p)) else p) for p in sys.argv) body += '

sudo ' + cmdLine + '

' htmlFilename = args.html or 'graph.html' writeHtmlFile(htmlFilename, 'Graph', '', body, includeDOCTYPE=False) # if DOCTYPE is included, scaling doesn't work properly print('Output written to ' + htmlFilename) if __name__ == "__main__": main()