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improve axis scaling and ticks for benchmark result plots

master
Constantin Fürst 3 months ago
parent
commit
436ce28804
  1. BIN
      benchmarks/benchmark-plots/plot-1dsa-throughput.pdf
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      benchmarks/benchmark-plots/plot-2dsa-throughput.pdf
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      benchmarks/benchmark-plots/plot-4dsa-throughput.pdf
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      benchmarks/benchmark-plots/plot-8cpu-throughput.pdf
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      benchmarks/benchmark-plots/plot-8dsa-throughput.pdf
  6. BIN
      benchmarks/benchmark-plots/plot-andrepeak-throughput.pdf
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      benchmarks/benchmark-plots/plot-average-throughput.pdf
  8. BIN
      benchmarks/benchmark-plots/plot-dsa-throughput-scaling.pdf
  9. 14
      benchmarks/benchmark-plotters/plot-perf-peakthroughput-bar.py
  10. BIN
      thesis/images/plot-1dsa-throughput.pdf
  11. BIN
      thesis/images/plot-2dsa-throughput.pdf
  12. BIN
      thesis/images/plot-4dsa-throughput.pdf
  13. BIN
      thesis/images/plot-8cpu-throughput.pdf
  14. BIN
      thesis/images/plot-8dsa-throughput.pdf
  15. BIN
      thesis/images/plot-andrepeak-throughput.pdf
  16. BIN
      thesis/images/plot-average-throughput.pdf
  17. BIN
      thesis/images/plot-dsa-throughput-scaling.pdf

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benchmarks/benchmark-plots/plot-1dsa-throughput.pdf

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benchmarks/benchmark-plots/plot-2dsa-throughput.pdf

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benchmarks/benchmark-plots/plot-4dsa-throughput.pdf

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benchmarks/benchmark-plots/plot-8cpu-throughput.pdf

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benchmarks/benchmark-plots/plot-8dsa-throughput.pdf

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benchmarks/benchmark-plots/plot-andrepeak-throughput.pdf

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benchmarks/benchmark-plots/plot-average-throughput.pdf

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benchmarks/benchmark-plots/plot-dsa-throughput-scaling.pdf

14
benchmarks/benchmark-plotters/plot-perf-peakthroughput-bar.py

@ -68,12 +68,13 @@ def plot_bar(table,node_config,display_x,display_y):
sns.barplot(x=x_label, y=y_label, data=table, palette="mako", errorbar="sd")
plt.ylim(0, 75)
plt.ylim(0, 70)
plt.yticks([15,30,45,60,65])
plt.xlabel(display_x)
plt.ylabel(display_y)
plt.savefig(os.path.join(output_path, f"plot-{node_config}-throughput.pdf"), bbox_inches='tight')
plt.show()
def PlotAndrePeakResults():
data_peakbench_andre = [
@ -147,10 +148,11 @@ if __name__ == "__main__":
]
scaling_df = pd.DataFrame(data_scaling)
sns.lineplot(x=x_dsacount, y=y_scaling, data=scaling_df, marker='o', linestyle='-', color='b', markersize=8)
plt.figure(figsize=(2, 3))
fig = sns.lineplot(x=x_dsacount, y=y_scaling, data=scaling_df, marker='o', linestyle='-', color='b', markersize=8)
plt.xticks([1,2,4,8])
plt.yticks([0.25,0.5,0.75,1.0])
plt.xlim(0,10)
plt.ylim(0,1.25)
plt.ylim(0.2,1.05)
plt.savefig(os.path.join(output_path, f"plot-dsa-throughput-scaling.pdf"), bbox_inches='tight')
plt.show()

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thesis/images/plot-1dsa-throughput.pdf

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thesis/images/plot-2dsa-throughput.pdf

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thesis/images/plot-4dsa-throughput.pdf

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thesis/images/plot-8cpu-throughput.pdf

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thesis/images/plot-8dsa-throughput.pdf

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thesis/images/plot-andrepeak-throughput.pdf

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thesis/images/plot-average-throughput.pdf

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thesis/images/plot-dsa-throughput-scaling.pdf

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