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

70 lines
2.4 KiB
Python

import sys
import numpy as np
sys.path.insert(0, 'tools')
from viz_theme import apply_monochrome, save_svg, load_csv
apply_monochrome()
import matplotlib.pyplot as plt
def read_data(rows):
ops = []
m512 = []; m512_err = []
m768 = []; m768_err = []
m1024 = []; m1024_err = []
for row in rows:
ops.append(row['op'])
m512.append(float(row['m512_sp']))
m512_err.append([float(row['m512_elo']), float(row['m512_ehi'])])
m768.append(float(row['m768_sp']))
m768_err.append([float(row['m768_elo']), float(row['m768_ehi'])])
m1024.append(float(row['m1024_sp']))
m1024_err.append([float(row['m1024_elo']), float(row['m1024_ehi'])])
m512_err = np.array(m512_err).T
m768_err = np.array(m768_err).T
m1024_err = np.array(m1024_err).T
return ops, m512, m512_err, m768, m768_err, m1024, m1024_err
DATA = "hand_simd.csv"
ops, m512, m512_err, m768, m768_err, m1024, m1024_err = read_data(load_csv(DATA))
fig, ax = plt.subplots(figsize=(10, 4))
bar_width = 0.25
colors = ['#333333', '#777777', '#bbbbbb']
labels = ['ML-KEM-512', 'ML-KEM-768', 'ML-KEM-1024']
x = np.arange(len(ops))
ax.bar(x - bar_width, m512, bar_width, label=labels[0], color=colors[0], yerr=m512_err, edgecolor='none')
ax.bar(x, m768, bar_width, label=labels[1], color=colors[1], yerr=m768_err, edgecolor='none')
ax.bar(x + bar_width, m1024, bar_width, label=labels[2], color=colors[2], yerr=m1024_err, edgecolor='none')
ax.set_xticks(x)
display_ops = [op.replace('gena', 'gen_a') for op in ops]
ax.set_xticklabels(display_ops, rotation=45, ha='right')
ax.set_yscale('log')
ax.set_ylabel("Speedup ref $\\to$ avx2 ($\\times$)")
ax.set_ylim(bottom=1, top=100)
import matplotlib.ticker as ticker
ax.yaxis.set_major_formatter(ticker.FuncFormatter(lambda y, pos: f"${int(y)}\\times$"))
ax.legend(loc='upper left', frameon=False, fontsize='small')
save_svg(
fig,
alt=(
"Grouped bar chart of hand-written AVX2 speedup over scalar "
"reference code, for nine ML-KEM operations at three parameter "
"sets."
),
desc=(
"Logarithmic axis, operations sorted by their ML-KEM-512 speedup. "
"The range runs from about 56 times for INVNTT and 52 times for "
"basemul down to about 1.4 times for noise sampling. The three "
"parameter sets track each other closely for every operation. "
"Confidence intervals are present but mostly narrower than the bar "
"edges."
),
)