ROCm/composable_kernel
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Plot a large set of benchmark results.

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This commit is contained in:
Ville Pietilä
2025-10-22 13:41:14 +00:00
parent df5d804f47
commit 5065ddd409
1 changed files with 3 additions and 9 deletions
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12
script/benchmark_ck_vs_ck_tile.py
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@@ -235,9 +235,7 @@ def run_analysis(results_file):
# Extend range to ensure we capture all data
bin_start = int(min_ratio // bin_width) * bin_width
bin_end = int(max_ratio // bin_width) * bin_width
# Create bin edges with 5% width, positioned so 100% falls between bins
bin_edges = np.arange(bin_start, bin_end + bin_width, bin_width)
bin_edges = np.arange(bin_start, bin_end, bin_width)
# Create the histogram data
counts, bins = np.histogram(performance_ratios, bins=bin_edges)
@@ -252,12 +250,9 @@ def run_analysis(results_file):
colors.append('green')
# Plot the histogram with custom colors
plt.bar(bin_edges[:-1], counts, width=4.5, color=colors, edgecolor='black',
plt.bar(bin_edges[:-1], counts, width=bin_width, color=colors, edgecolor='black',
alpha=0.7, align='edge')
# Add parity line at 100%
#plt.axvline(x=100, color='black', linestyle='--', linewidth=2, label='Parity (100%)')
plt.xlabel('CK Tile Performance (% of CK)')
plt.ylabel('Number of Test Cases')
plt.title('CK Tile vs CK Performance Distribution\n(>100% = CK Tile Faster, <100% = CK Faster)')
@@ -266,8 +261,7 @@ def run_analysis(results_file):
from matplotlib.patches import Patch
legend_elements = [
Patch(facecolor='red', alpha=0.7, label='CK Faster (<100%)'),
Patch(facecolor='green', alpha=0.7, label='CK Tile Faster (>100%)'),
plt.Line2D([0], [0], color='black', linestyle='--', label='Parity (100%)')
Patch(facecolor='green', alpha=0.7, label='CK Tile Faster (>100%)')
]
plt.legend(handles=legend_elements)