Harnessing Custom AI Accelerators

This chapter examines the technical intricacies of running programs on custom AI accelerators, utilizing frameworks like PyTorch and the AWS Neuron SDK. It discusses the optimization of model representation, kernel usage, and the seamless integration of advanced chips within the SageMaker environment. Key advancements, including the Tranium 2 chip and ultra servers, are highlighted to showcase their impact on the performance of large language models.

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