#c_lang #convolutional_neural_network #convolutional_neural_networks #cpu #inference #inference_optimization #matrix_multiplication #mobile_inference #multithreading #neural_network #neural_networks #simd

https://github.com/google/XNNPACK

#java #adjacency #adjacency_matrix #algorithm #algorithms #dijkstra #dynamic_programming #edmonds_karp_algorithm #geometry #graph_theory #linear_algebra #mathematics #matrix_multiplication #maxflow #nlog #search_algorithm #search_algorithms #sorting_algorithms #strings #traveling_salesman #tree_algorithms

https://github.com/williamfiset/Algorithms

#c_lang #convolutional_neural_network #convolutional_neural_networks #cpu #inference #inference_optimization #matrix_multiplication #mobile_inference #multithreading #neural_network #neural_networks #simd

XNNPACK is a powerful tool that helps make neural networks run faster on various devices like smartphones, computers, and Raspberry Pi boards. It supports many different types of processors and operating systems, making it very versatile. XNNPACK doesn't work directly with users but instead helps other machine learning frameworks like TensorFlow Lite, PyTorch, and ONNX Runtime to perform better. This means your apps and programs that use these frameworks can run neural networks more quickly and efficiently, which is beneficial because it saves time and improves performance.

https://github.com/google/XNNPACK