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Training Compute (petaFLOPS) 101⁰ 109 108 107 106 105 104 103 10² Modern Al is a Data Center Scale Computing Workload Data centers are becoming Al factories: Data as input, intelligence as output All Al Models Excluding Transformers: 8X / 2yrs Transformer Al Models: 275X / 2yrs AlexNet Seq2Seq InceptionV3 Resnet ● VGG-19 Xception ● ResNeXt Microsoft T-NLG ● GPT-2 · Megatron XLNet. ● GPT-1 Transformer ELMO DenseNet201 BERT Large Megatron-Turing NLG 530B GPT-3 ● Wav2Vec 2.0 MOCO ResNet50 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Al Training Computational Requirements 2022 Large Language Models, based on the Transformer architecture, are one of today's most important advanced Al technologies, involving up to trillions of parameters that learn from text. Developing them is an expensive, time-consuming process that demands deep technical expertise, distributed data center-scale infrastructure, and a full-stack accelerated computing approach. Fueling Giant-Scale Al Infrastructure NVIDIA compute & networking GPU | DPU | CPU NVIDIA

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