How to Use Keras-Based Multi-GPU
Keras is an open-source neural network library written in Python. It is a high-level neural network API that can run on top of MXNet, Deeplearning4j, TensorFlow, Microsoft Cognitive Toolkit, or Theano. In the NEURON system, queues like cas_v100_2, cas_v100nv_4, cas_v100nv_8, and amd_a100nv_8 are equipped with 2, 4, or 8 GPUs per node, providing an environment where multiple GPUs can be used for neural network training even within a single node.
A. Code modifications and job submission methods for using Multi-GPU
1. Add the [from keras.utils import multi_gpu_model] module
2. Declare the use of multi-GPU in the code
※ Set the number of GPUs to the desired amount. (For example, in a cas_v100nv_4 node, set gpus=4)
3. Job submission script
Last updated on November 11, 2024.
Last updated