ROCm/composable_kernel
1
0
Fork 0
mirror of https://github.com/ROCm/composable_kernel.git synced 2026-07-15 11:34:54 +00:00
Code Issues Packages Projects Releases Wiki Activity

Script improvements.

Browse Source
This commit is contained in:
Ville Pietilä
2025-07-28 12:51:14 +00:00
parent 7ff0850e24
commit ddc090b766
1 changed files with 14 additions and 6 deletions
Download Patch File Download Diff File Expand all files Collapse all files

20
script/analyze_conv_tests.py
View File

@@ -573,7 +573,7 @@ def plot_performance(fixed_split_k_tflops, best_occupancy_split_k_tflops, gemm_m
norm=plt.Normalize(vmin=0, vmax=200)) # Normalize colors: blue (<100%), red (>100%)
plt.colorbar(label='Performance (%)')
plt.title(title, fontsize=title_size)
plt.xlabel('log(K)', fontsize=14)
plt.xlabel('$\\log(K_{\\mathrm{gemm}})$', fontsize=14)
plt.ylabel('log(Arithmetic Intensity)', fontsize=14)
plt.grid(True, linestyle='--', alpha=0.7)
plt.tight_layout()
@@ -582,6 +582,14 @@ def plot_performance(fixed_split_k_tflops, best_occupancy_split_k_tflops, gemm_m
fp32_ridge_point = np.log10(653.7 / 5.3)
plt.axhline(y=fp16_ridge_point, color='green', linestyle='--', label='FP16/BF16 Ridge Point')
plt.axhline(y=fp32_ridge_point, color='black', linestyle='--', label='FP32 Ridge Point')
plt.legend()
plt.text(0.05, 0.05, "Memory bound", transform=plt.gca().transAxes,
fontsize=12, color='black', verticalalignment='bottom',
bbox=dict(boxstyle='round', facecolor='white', alpha=0.8))
plt.text(0.05, 0.95, "Compute bound", transform=plt.gca().transAxes,
fontsize=12, color='black', verticalalignment='top',
bbox=dict(boxstyle='round', facecolor='white', alpha=0.8))
file_name = os.path.join(output_dir, f'performance_heatmap_k_ai{suffix}.png')
plt.savefig(file_name, dpi=150)
@@ -806,11 +814,11 @@ def plot_perf_for_all_solvers(solvers_per_conv_shape, output_dir, suffix, op_nam
plt.ylabel('Count', fontsize=12)
# Add explanation text middle top
y_loc = 0.9*max(counts)
explanation = "Candidate split-K values ['best occupancy', 1, 2, 4, 8, 16, 32, 64, 128].\n" \
"Ranking of 'best occupancy' value for each solver instance\n" \
"Rank 1 is the best, rank 2 is second best, etc."
plt.text(2.5, y_loc, explanation)
# y_loc = 0.9*max(counts)
# explanation = "Candidate split-K values ['best occupancy', 1, 2, 4, 8, 16, 32, 64, 128].\n" \
# "Ranking of 'best occupancy' value for each solver instance\n" \
# "Rank 1 is the best, rank 2 is second best, etc."
# plt.text(2.5, y_loc, explanation)
# Set x-ticks at the center of each bar
plt.xticks(bin_centers, range(1, max(ranking) + 1))