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Prepare dataframe format for Latex plots

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Derek Christ
2024-02-28 16:26:37 +01:00
committed by Derek Christ
parent 3d9533c10c
commit 353488837c
2 changed files with 33 additions and 23 deletions
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47
pim_plots.py
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@@ -3,33 +3,46 @@ import seaborn as sns
import pandas as pd import pandas as pd
import numpy as np import numpy as np
df = pd.read_csv("pim_results.csv") from pathlib import Path
workloads = df["workload"].unique() df = pd.read_csv("pim_results.csv")
sns.set_theme() sns.set_theme()
def calc_speedup(x): def calc_speedup(x):
return x.iat[0] / x.iat[1] return x.iat[0] / x.iat[1]
for workload in df["workload"].unique(): workload_sets = [["vadd", "vmul", "haxpy"], ["gemv", "gemv_layers"]]
workload_filter = df["workload"] == workload
filtered_df = df[workload_filter] for workload_set in workload_sets:
preprocessed_df = filtered_df.groupby(["workload", "level", "frequency"], as_index=False).agg({"ticks": calc_speedup}).rename(columns={"ticks":"speedup"}) workload_filter = df["workload"].isin(workload_set)
# print(preprocessed_df) for frequency in df["frequency"].unique():
# preprocessed_df.to_csv("plot.csv", index=False) frequency_filter = df["frequency"] == frequency
g = sns.catplot( filtered_df = df[workload_filter & frequency_filter]
data=preprocessed_df, kind="bar", print(filtered_df)
x="level", y="speedup", hue="frequency", preprocessed_df = filtered_df.groupby(["workload", "level", "frequency"], as_index=False).agg({"ticks": calc_speedup}).rename(columns={"ticks":"speedup"})
palette="dark", alpha=.6, height=6
)
g.despine(left=True) print(preprocessed_df)
g.set_axis_labels("", "Speedup") # preprocessed_df.to_csv("plot.csv", index=False)
g.set(title=workload)
g.legend.set_title("") g = sns.catplot(
data=preprocessed_df, kind="bar",
x="level", y="speedup", hue="workload",
palette="dark", alpha=.6, height=6
)
g.despine(left=True)
g.set_axis_labels("", "Speedup")
g.set(title=frequency)
g.legend.set_title("")
for workload in workload_set:
export_df = preprocessed_df[preprocessed_df["workload"] == workload]
filename = f"{workload}_{frequency}.csv"
directory = Path("plots_out")
export_df.to_csv(directory / filename, index=False)
plt.show() plt.show()

5
simulation_script.py
View File

@@ -49,7 +49,7 @@ workloads = [
"vmul", "vmul",
"haxpy", "haxpy",
"gemv", "gemv",
# "gemv_layers", "gemv_layers",
] ]
systems = [ systems = [
@@ -63,9 +63,6 @@ for frequency in ["3GHz", "100GHz"]:
for level in ["X1", "X2", "X3", "X4"]: for level in ["X1", "X2", "X3", "X4"]:
for system in systems: for system in systems:
for workload in workloads: for workload in workloads:
if workload == "gemv_layers" and level != "X4":
continue
executable = workload executable = workload
if system == "HBM": if system == "HBM":