This contains my bachelors thesis and associated tex files, code snippets and maybe more. Topic: Data Movement in Heterogeneous Memories with Intel Data Streaming Accelerator
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import os
import json
import pandas as pd
from pandas.core.ops import methods
from typing import List
import seaborn as sns
import matplotlib.pyplot as plt
runid = "Run ID"
x_label = "Destination Node"
y_label = "Source Node"
v_label = "Throughput"
title = "Copy Throughput for 1GiB Elements running on SRC Node"
index = [ runid, x_label, y_label]
data = []
def mean_without_outliers(x):
return x.sort_values()[2:-2].mean()
def calc_throughput(size_bytes,time_ns):
time_seconds = time_ns * 1e-9
size_gib = size_bytes / (1024 ** 3)
throughput_gibs = size_gib / time_seconds
return throughput_gibs
def index_from_element(value,array):
for (idx,val) in enumerate(array):
if val == value: return idx
return 0
def load_time_mesurements(file_path):
with open(file_path, 'r') as file:
data = json.load(file)
iterations = data["list"][0]["task"]["iterations"]
return {
"total": data["list"][0]["report"]["time"]["total"] / iterations,
"combined": data["list"][0]["report"]["time"]["combined"],
"submission": data["list"][0]["report"]["time"]["submission"],
"completion": data["list"][0]["report"]["time"]["completion"]
}
def process_file_to_dataset(file_path, src_node, dst_node):
data_size = 1024*1024*1024
try:
time = [load_time_mesurements(file_path)["total"]]
run_idx = 0
for t in time:
data.append({ runid : run_idx, x_label : dst_node, y_label : src_node, v_label: calc_throughput(data_size, t)})
run_idx = run_idx + 1
except FileNotFoundError:
return
def main():
folder_path = "benchmark-results/"
for src_node in range(16):
for dst_node in range(16):
file = os.path .join(folder_path, f"copy-n{src_node}ton{dst_node}-1gib-1e.json")
process_file_to_dataset(file, src_node, dst_node)
df = pd.DataFrame(data)
df.set_index(index, inplace=True)
data_pivot = df.pivot_table(index=y_label, columns=x_label, values=v_label)
sns.heatmap(data_pivot, annot=True, cmap="rocket_r", fmt=".0f")
plt.title(title)
plt.savefig(os.path.join(folder_path, "plot-perf-peakthroughput.png"), bbox_inches='tight')
plt.show()
if __name__ == "__main__":
main()