Optical Neuromorphic Eikonal Solver - Benchmark Datasets
# Optical Neuromorphic Eikonal Solver - Benchmark Datasets Benchmark datasets for evaluating GPU-accelerated pathfinding algorithms. ## Content 5 synthetic pathfinding test cases: - sparse_128.npz (128×128, 10% obstacles) - medium_256.npz (256×256, 20% obstacles) - gradient_256.npz (256×256, gradien...
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2025
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| Summary: | # Optical Neuromorphic Eikonal Solver - Benchmark Datasets Benchmark datasets for evaluating GPU-accelerated pathfinding algorithms. ## Content 5 synthetic pathfinding test cases: - sparse_128.npz (128×128, 10% obstacles) - medium_256.npz (256×256, 20% obstacles) - gradient_256.npz (256×256, gradient speeds) - maze_511.npz (511×511, perfect maze) - complex_512.npz (512×512, 30% obstacles) Plus benchmark results showing GPU solver performance. ## Performance - 134.9× average speedup vs CPU Dijkstra - 0.64% mean absolute error - 1.025× optimal path length - 2-4ms per query on 512×512 grids ## Format NumPy .npz archives containing: - obstacles: (H,W) float32 array - speeds: (H,W) float32 array - source: (2,) int32 array - target: (2,) int32 array - metadata: JSON string See DATASETS.md for complete specification. ## Links - Code: https://github.com/Agnuxo1/Optical-Neuromorphic-Computing-for-Real-Time-Pathfinding-A-GPU-Accelerated-Eikonal-Solver - Paper: https://github.com/Agnuxo1/Optical-Neuromorphic-Computing-for-Real-Time-Pathfinding-A-GPU-Accelerated-Eikonal-Solver/blob/main/optical_neuromorphic_paper.html - Datasets: https://huggingface.co/datasets/Agnuxo/optical-neuromorphic-eikonal-benchmarks - Demo: https://huggingface.co/spaces/Agnuxo/optical-neuromorphic-pathfinding-demo ## Citation See README or paper for citation information. |
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