Tag: Memory Optimization

Gradient Accumulation: A Comprehensive Technical Guide to Training Large-Scale Models on Memory-Constrained Hardware

Posted on by uplatzblog

Executive Summary Gradient accumulation is a pivotal technique in modern deep learning, designed to enable the training of models with large effective batch sizes on hardware constrained by limited memory.1 Read More …

FlashAttention: A Paradigm Shift in Hardware-Aware Transformer Efficiency

Posted on by uplatzblog

The Tyranny of Quadratic Complexity: Deconstructing the Transformer Attention Bottleneck The Transformer architecture, a cornerstone of modern artificial intelligence, is powered by the self-attention mechanism. While remarkably effective, this mechanism Read More …