levineuwirth.org/content/essays/where-does-simd-help-post-q.../figures/fig_decomp.py

71 lines
2.5 KiB
Python

import sys
import os
import csv
import numpy as np
sys.path.insert(0, 'tools')
from viz_theme import apply_monochrome, save_svg
apply_monochrome()
import matplotlib.pyplot as plt
def read_data(filepath):
ops = []
refnv = []; refnv_err = []
ref = []; ref_err = []
avx2 = []; avx2_err = []
with open(filepath, 'r') as f:
reader = csv.DictReader(f)
for row in reader:
ops.append(row['op'])
refnv.append(float(row['refnv_sp']))
refnv_err.append([float(row['refnv_elo']), float(row['refnv_ehi'])])
ref.append(float(row['ref_sp']))
ref_err.append([float(row['ref_elo']), float(row['ref_ehi'])])
avx2.append(float(row['avx2_sp']))
avx2_err.append([float(row['avx2_elo']), float(row['avx2_ehi'])])
refnv_err = np.array(refnv_err).T
ref_err = np.array(ref_err).T
avx2_err = np.array(avx2_err).T
return ops, refnv, refnv_err, ref, ref_err, avx2, avx2_err
base_path = "content/essays/where-does-simd-help-post-quantum-cryptography/figures/data"
params = [("ML-KEM-512", f"{base_path}/decomp_mlkem512.csv"),
("ML-KEM-768", f"{base_path}/decomp_mlkem768.csv"),
("ML-KEM-1024", f"{base_path}/decomp_mlkem1024.csv")]
fig, axes = plt.subplots(1, 3, figsize=(12, 4), sharey=True)
bar_width = 0.25
colors = ['#333333', '#777777', '#bbbbbb']
labels = ['O3 (no auto-vec)', 'O3 + auto-vec', 'O3 + hand SIMD']
for i, (title, filepath) in enumerate(params):
ops, refnv, refnv_err, ref, ref_err, avx2, avx2_err = read_data(filepath)
ax = axes[i]
x = np.arange(len(ops))
ax.bar(x - bar_width, refnv, bar_width, label=labels[0], color=colors[0], yerr=refnv_err, edgecolor='none')
ax.bar(x, ref, bar_width, label=labels[1], color=colors[1], yerr=ref_err, edgecolor='none')
ax.bar(x + bar_width, avx2, bar_width, label=labels[2], color=colors[2], yerr=avx2_err, edgecolor='none')
ax.set_title(title, pad=10)
ax.set_xticks(x)
# Format xticklabels to replace iDec, iEnc, iKeypair, gena
display_ops = [op.replace('gena', 'gen_a') for op in ops]
ax.set_xticklabels(display_ops, rotation=45, ha='right')
ax.set_yscale('log')
if i == 0:
ax.set_ylabel("Speedup over -O0 ($\times$)")
# Tick formatting
ax.set_ylim(bottom=1, top=500)
import matplotlib.ticker as ticker
ax.yaxis.set_major_formatter(ticker.FuncFormatter(lambda y, pos: f"${int(y)}\\times$"))
axes[-1].legend(loc='upper right', frameon=False, fontsize='small')
save_svg(fig)