50 lines
1.3 KiB
Python
50 lines
1.3 KiB
Python
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import os
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import json
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import matplotlib.pyplot as plt
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import numpy as np
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from tqdm import tqdm
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from datetime import datetime
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num_runs = 100
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dict_of_dict_of_lists = dict()
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graph_repo="data"
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os.makedirs(graph_repo, exist_ok=True)
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fancy_num_runs = range(0, num_runs, 1)
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for run_id in tqdm(fancy_num_runs):
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filename = graph_repo+"/run"+str(run_id)+".json"
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with open(filename) as f:
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dict_of_dict_of_lists[run_id] = json.load(f)
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l1_all = []
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l2_all = []
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l3_all = []
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mem_all = []
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for run_id in tqdm(fancy_num_runs):
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l1_all += dict_of_dict_of_lists[run_id]['1']
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l2_all += dict_of_dict_of_lists[run_id]['2']
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l3_all += dict_of_dict_of_lists[run_id]['3']
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mem_all += dict_of_dict_of_lists[run_id]['4']
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#
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# MAX 300
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#
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fig_all = plt.figure(figsize=(11.25, 7.5))
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ax_all = fig_all.add_subplot(1,1,1)
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ax_all.set_xlabel("Access Time")
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ax_all.set_ylabel("Number of Samples")
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ax_all.hist(l1_all, label="L1", bins=np.arange(0, 300 ), alpha=0.5)
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ax_all.hist(l2_all, label="L2", bins=np.arange(0, 300 ), alpha=0.5)
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ax_all.hist(l3_all, label="L3", bins=np.arange(0, 300 ), alpha=0.5)
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ax_all.hist(mem_all, label="DRAM", bins=np.arange(0, 300 ), alpha=0.5)
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fig_all.legend()
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os.makedirs("graphs", exist_ok=True)
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now = datetime.now()
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date_time = now.strftime("%m:%d:%Y_%H:%M:%S")
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fig_all.savefig(str("graphs/"+date_time+".pdf"))
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plt.close(fig_all)
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