Tag Archives: Activation Checkpointing
Optimization Techniques for Deep Learning: Enhancing Performance and Efficiency
Introduction Training deep neural networks presents several challenges related to memory constraints, computational resources, and convergence issues. This document explores advanced techniques that address these challenges, including optimization algorithms like Stochastic Gradient Descent (SGD), SGD with Momentum, Adam, LARS, and LAMB, as well as methods such as gradient accumulation and activation checkpointing. Optimizing the Loss…