Caffe is a deep learning framework developed by the Berkeley Vision and Learning Center (BVLC) and one of the most popular community frameworks for image recognition. Caffe is often used as a benchmark together with AlexNet*, a neural network topology for image recognition, and ImageNet*, a database of labeled images.
Cython* is a superset of Python* that additionally supports C functions and C types on variable and class attributes. Cython generates C extension modules, which can be used by the main Python program using the import statement.
Learn how to write an MPI program in Python*, and take advantage of Intel® multicore architectures using OpenMP threads and Intel® AVX512 instructions.
The TensorFlow* image classification sample codes below describe a step-by-step approach to modify the code in order to scale the deep learning training across multiple nodes of HPC data centers.