mirror of https://github.com/gnss-sdr/gnss-sdr
44 lines
1.7 KiB
Python
44 lines
1.7 KiB
Python
#!/usr/bin/env python
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# Copyright (C) 2010-2020 (see AUTHORS file for a list of contributors)
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#
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# GNSS-SDR is a software-defined Global Navigation Satellite Systems receiver
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#
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# This file is part of GNSS-SDR.
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#
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# SPDX-License-Identifier: GPL-3.0-or-later
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# This script is used to compare the generic kernels to the highest performing kernel, for each operation
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# Run:
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# ./volk_gnsssdr_profile -j volk_gnsssdr_results.json
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# Then run this script under python3
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import matplotlib.pyplot as plt
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import numpy as np
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import json
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filename = 'volk_gnsssdr_results.json'
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operations = []
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metrics = []
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with open(filename) as json_file:
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data = json.load(json_file)
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for test in data['volk_gnsssdr_tests']:
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if ('generic' in test['results']) or ('u_generic' in test['results']): # some dont have a generic kernel
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operations.append(test['name'][13:]) # remove volk_gnsssdr_ prefix that they all have
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extension_performance = []
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for key, val in test['results'].items():
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if key not in ['generic', 'u_generic']: # exclude generic results, when trying to find fastest time
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extension_performance.append(val['time'])
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try:
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generic_time = test['results']['generic']['time']
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except:
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generic_time = test['results']['u_generic']['time']
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metrics.append(extension_performance[np.argmin(extension_performance)]/generic_time)
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plt.bar(np.arange(len(metrics)), metrics)
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plt.hlines(1.0, -1, len(metrics), colors='r', linestyles='dashed')
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plt.axis([-1, len(metrics), 0, 2])
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plt.xticks(np.arange(len(operations)), operations, rotation=90)
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plt.ylabel('Time taken of fastest kernel relative to generic kernel')
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plt.show()
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