About this document
Hybrid Parallelization for Deep Learning by dannyafolabs is a document available to read on EtoBox.
This document presents a hybrid parallelization approach for distributed and scalable training of Deep Neural Networks (DNNs), combining model and data parallelism to enhance efficiency. The proposed method includes a Genetic Algorithm Based Heuristic Resources Allocation (GABRA) mechanism for optimal GPU resource distribution, achieving a 20% improvement in training time compared to existing methods. The approach is validated through a case study on a 3D Residual Attention Deep Neural Network for Alzheimer
- Author
- dannyafolabs
- Language
- EN