Emergency Corrections
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+5574
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@@ -314,6 +314,8 @@ ax.set_ylim(0.6, 70)
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ax.set_xlabel("Operational Intensity [flops/byte]",
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ax.set_xlabel("Operational Intensity [flops/byte]",
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fontweight="bold",
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fontweight="bold",
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fontsize=9)
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fontsize=9)
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ax.set_xticklabels(ax.get_xticklabels(), fontweight="bold")
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ax.set_yticklabels(ax.get_yticklabels(), fontweight="bold")
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# ax.set_ylabel("Performance [flops/cycle]", fontweight="bold", fontsize=9)
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# ax.set_ylabel("Performance [flops/cycle]", fontweight="bold", fontsize=9)
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plt.title(
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plt.title(
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'Performance [flops/cycle]\nCPU: AMD Ryzen AI 7 350 w/ Radeon 860M @ 2 GHz\nCompiler: g++ (Debian 15.2.0-17) 15.2.0\nFlags: -O3 -march=native -std=c++23 -Wall -Wextra -flto',
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'Performance [flops/cycle]\nCPU: AMD Ryzen AI 7 350 w/ Radeon 860M @ 2 GHz\nCompiler: g++ (Debian 15.2.0-17) 15.2.0\nFlags: -O3 -march=native -std=c++23 -Wall -Wextra -flto',
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@@ -451,10 +453,10 @@ num_ticks = 7
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linear_positions = np.linspace(xlim_log[0], xlim_log[1], num_ticks)
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linear_positions = np.linspace(xlim_log[0], xlim_log[1], num_ticks)
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tick_positions = 10**linear_positions
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tick_positions = 10**linear_positions
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ax.set_xticks(tick_positions)
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ax.set_xticks(tick_positions)
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ax.set_xticklabels(["50", "100", "200", "500", "1k", "2k", "5k"])
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ax.set_xticklabels(["50", "100", "200", "500", "1k", "2k", "5k"], fontweight="bold")
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ax.set_yticks([1, 2, 5, 10, 20])
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ax.set_yticks([1, 2, 5, 10, 20])
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ax.set_yticklabels(["1x", "2x", "5x", "10x", "20x"])
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ax.set_yticklabels(["1x", "2x", "5x", "10x", "20x"], fontweight="bold")
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ax.tick_params(axis='both', which='minor', length=0)
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ax.tick_params(axis='both', which='minor', length=0)
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ax.tick_params(axis='both', which='major', length=4)
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ax.tick_params(axis='both', which='major', length=4)
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@@ -0,0 +1,3 @@
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pandas
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numpy
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matplotlib
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