Introduction to Ironwood

  • Ironwood is Google's 7th Generation Tensor Processing Unit (TPU) designed to manage Artificial Intelligence (AI) models.
  • Google's latest chip, Ironwood, aims to facilitate proactive AI by optimising "thinking models" like Large Language Models (LLMs) and Mixture of Experts (MoEs).
  • Ironwood delivers insights rather than merely processing data.

 

Key Features of Google Ironwood TPU

  • Ironwood TPU can support up to 9,216 chips per pod, providing 42.5 Exaflops of compute, which surpasses the power capacity of El Capitan, the world's largest supercomputer, by more than 24x.
  • - Ironwood demonstrates unprecedented energy efficiency, doubling the performance per watt compared to the previous generation and utilising advanced liquid cooling to maximise power efficacy.
  • As an integral part of Google Cloud's Hypercomputer architecture, Ironwood can scale generative AI models and meet the requirements of complex AI tasks.

 

Overview of Processing Units 

  • Serving as the brain of a computer, processing units perform tasks akin to human cognitive functions - from problem-solving and calculation to image processing and messaging.
  • Notable types of Processing Units include the Central Processing Unit (CPU), Graphics Processing Unit (GPU), and Tensor Processing Unit (TPU).

 

Understanding Tensor Processing Units (TPUs)

  • TPUs, a subset of Application Specific Integrated Circuits (ASIC), are purpose-built to manage a specific range of tasks.
  • Compared to CPUs and GPUs, TPUs are further specialised, being devised particularly to hasten machine learning workloads and assist AI-specific computations.
  • Powering Google's key AI services such as Search, YouTube, and DeepMind’s language models, TPUs excel at managing significant datasets and conducting complicated neural networks, thereby enabling quicker training of AI models than conventional processors.