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77 lines
2.4 KiB
77 lines
2.4 KiB
import os
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import json
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import pandas as pd
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from pandas.core.ops import methods
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import seaborn as sns
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import matplotlib.pyplot as plt
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x_label = "Copy Type"
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y_label = "Time in Microseconds"
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var_label = "Thread Counts"
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thread_counts = ["1t", "2t", "4t", "8t", "12t"]
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thread_counts_nice = ["1 Thread", "2 Threads", "4 Threads", "8 Threads", "12 Threads"]
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engine_counts = ["1e", "4e"]
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engine_counts_nice = ["1 Engine per Group", "4 Engines per Group"]
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data = {
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x_label : thread_counts_nice,
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engine_counts_nice[0] : [],
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engine_counts_nice[1] : [],
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}
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def index_from_element(value,array):
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for (idx,val) in enumerate(array):
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if val == value: return idx
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return 0
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# Function to load and process the JSON file for the multi-threaded benchmark
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def load_and_process_mt_json(file_path):
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with open(file_path, 'r') as file:
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data = json.load(file)
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# Extracting count from JSON structure
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count = data["count"]
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# Extracting time from JSON structure for elements 0 to count
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times = [data["list"][i]["report"]["time"]["combined_avg"] for i in range(count)]
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# Calculating the average of times
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average_time = sum(times) / count
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return average_time
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# Function to plot the graph for the new benchmark
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def plot_mt_graph(file_paths, engine_label):
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times = []
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for file_path in file_paths:
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# Load and process JSON file for the new benchmark
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time_microseconds = load_and_process_mt_json(file_path)
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times.append(time_microseconds)
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engine_index = index_from_element(engine_label,engine_counts)
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engine_nice = engine_counts_nice[engine_index]
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data[engine_nice] = times
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# Main function to iterate over files and create plots for the new benchmark
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def main():
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folder_path = "benchmark-results/mtsubmit-bench/" # Replace with the actual path to your folder
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for engine_label in engine_counts:
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mt_file_paths = [os.path.join(folder_path, f"mtsubmit-{thread_count}-{engine_label}.json") for thread_count in thread_counts]
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plot_mt_graph(mt_file_paths, engine_label)
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df = pd.DataFrame(data)
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dfm = pd.melt(df, id_vars=x_label, var_name=var_label, value_name=y_label)
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sns.catplot(x=x_label, y=y_label, hue=var_label, data=dfm, kind='bar', height=5, aspect=1, palette="viridis")
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plt.savefig(os.path.join(folder_path, "plot-cost-mtsubmit.png"))
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plt.show()
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if __name__ == "__main__":
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main()
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