How To Take Full Advantage Of GPUs In Large Language Models

“Training GPT-3 with 175 billion parameters would require approximately 36 years with 8 V100 GPUs.” Training large machine learning models calls for huge compute power (~in hundreds of exaflops), efficient memory management for a reduced memory footprint and other tweaks. But, language models have grown at a great pace. In a span of two years, […]