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eo-processor Benchmark Report

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Key Value
Python 3.10.18
Platform macOS-15.6.1-arm64-arm-64bit
Group distances
Functions euclidean_distance, manhattan_distance, chebyshev_distance, minkowski_distance
Loops 2
Warmups 1
Seed 42
Compare NumPy True
Height 2048
Width 2048
Time 12
Points A 800
Points B 600
Point Dim 32

Results

| Function | Mean (ms) | StDev (ms) | Min (ms) | Max (ms) | Elements | Rust Throughput (M elems/s) | NumPy Throughput (M elems/s) | Speedup vs NumPy | Shape | |----------|-----------|------------|----------|----------|----------|------------------------|------------------|-------| | euclidean_distance | 1.85 | 0.00 | 1.85 | 1.85 | 480,000 | 259.41 | 325.24 | 0.80x | N=800, M=600, D=32 | | manhattan_distance | 2.57 | 0.14 | 2.43 | 2.71 | 480,000 | 186.61 | 13.93 | 13.40x | N=800, M=600, D=32 | | chebyshev_distance | 2.67 | 0.09 | 2.58 | 2.76 | 480,000 | 179.79 | 11.01 | 16.33x | N=800, M=600, D=32 | | minkowski_distance | 22.62 | 0.07 | 22.55 | 22.69 | 480,000 | 21.22 | 1.97 | 10.78x | N=800, M=600, D=32 |

Speedup vs NumPy = (NumPy mean time / Rust mean time); values > 1 indicate Rust is faster.