2d981a20c1
Improves concurrency, fixes memory out of bounce issue in robin hood sort. Adds report and plots notebook.
97 lines
3.7 KiB
Python
Executable File
97 lines
3.7 KiB
Python
Executable File
#!/usr/bin/env python
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import matplotlib.pyplot as plt
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import subprocess
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import argparse
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from pathlib import Path
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def run_experiment(output_file, build_dir):
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# The number of threads is not currently used, it's just here in case you want to parallelize your code.
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for radix in [-3, -2, -1, 1, 2, 4, 6, 8, 10, 12]:
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# for radix in [-2, -1, 4, 6, 8, 12]:
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# for radix in [10]:
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for threads in [1, 2, 4, 8, 12, 16]:
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# for threads in [1]:
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# for size in [1e2, 1e3, 1e4 + 1, 1e5, 1e6 - 1, 1e7]:
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for size in [1e2, 1e3, 1e4 + 1, 1e5, 1e6 - 1, 1e7, 1e8, 2 * 1e8]:
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# for size in [2 * 1e8]:
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print("Measuring p=" + str(threads) + " n=" + str(size) + " r=" + str(radix))
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executable = Path(build_dir) / "Sorter"
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returncode = subprocess.call([executable, str(size), str(threads), str(radix)], stdout=output_file)
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if returncode != 0:
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print("Program crashed")
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def make_plot(result_file):
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plots = dict()
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maxDuration = 0
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for line in result_file:
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if line.startswith("RESULT"):
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line = line[len("RESULT "):].strip()
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parts = line.split()
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measurement = {}
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for part in parts:
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key, value = part.split('=')
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measurement[key] = value
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n = int(round(int(measurement["n"]), -1))
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t = int(measurement["t"])
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r = int(measurement["r"])
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name = measurement["name"]
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durationNanoseconds = int(measurement["durationNanoseconds"])
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constructorNanoseconds = int(measurement["constructorNanoseconds"])
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if t not in plots:
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plots[t] = dict()
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if name not in plots[t]:
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plots[t][name] = list()
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plots[t][name + " (constructor)"] = list()
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plots[t][name].append((n, durationNanoseconds / n))
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plots[t][name + " (constructor)"].append((n, constructorNanoseconds / n))
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maxDuration = max(maxDuration, max(durationNanoseconds, constructorNanoseconds))
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fig, axs = plt.subplots(len(plots))
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for i, t in enumerate(plots):
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if len(plots) > 1:
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axs[i].set_title(f"#p={t}")
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for name in plots[t]:
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axs[i].plot(*zip(*plots[t][name]), label=name, marker='x')
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axs[i].plot(*zip(*plots[t][name]), label=name + " (constructor)", marker='+')
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axs[i].set_xscale('log')
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else:
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axs.plot(*zip(*plots[t][name]), label=name, marker='x')
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axs.plot(*zip(*plots[t][name]), label=name + " (constructor)", marker='+')
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axs.set_xscale('log')
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if len(plots) > 1:
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for ax in axs.flat:
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ax.set(xlabel='n', ylabel='Running time per element (ns)')
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ax.legend()
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else:
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axs.set(xlabel='n', ylabel='Running time per element (ns)')
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axs.legend()
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plt.tight_layout()
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plt.savefig("plot.pdf")
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def main():
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parser = argparse.ArgumentParser(description='evaluation tools')
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# subcommands run and plot
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subparsers = parser.add_subparsers(dest='command')
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run_parser = subparsers.add_parser('run')
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run_parser.add_argument('output_file', type=argparse.FileType('w'), help='output file')
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run_parser.add_argument("--build-dir", default="build", help="build directory")
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plot_parser = subparsers.add_parser('plot')
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plot_parser.add_argument('result_file', type=argparse.FileType('r'), help='result file')
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args = parser.parse_args()
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if args.command == 'run':
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run_experiment(args.output_file, args.build_dir)
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elif args.command == 'plot':
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make_plot(args.result_file)
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else:
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parser.print_help()
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if __name__ == "__main__":
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main()
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