Tensor Processing Unit (TPU)

GS3 – Science & Technology

Context:

Google recently unveiled a new computer chip named Ironwood, marking the launch of its 7th generation Tensor Processing Unit (TPU). These chips are specifically engineered to power Artificial Intelligence (AI) models. Processing units serve as the central hardware components that drive computing operations.

What is a TPU?

A Tensor Processing Unit (TPU) is a specialized type of Application-Specific Integrated Circuit (ASIC) — meaning it’s designed to carry out a limited set of highly focused tasks.
First introduced by Google in 2015, TPUs were purpose-built to accelerate Machine Learning (ML) workloads.

TPUs play a central role in many of Google’s AI-driven services such as Search, YouTube, and DeepMind’s large language models.
They are optimized to process tensors — the fundamental data structures used in machine learning computations.

Thanks to their design, TPUs can handle massive amounts of data and execute complex neural networks quickly and efficiently. This makes them ideal for the training and deployment of advanced AI models.

Neural Networks, or Artificial Neural Networks, are algorithms inspired by the structure of the human brain. They are a key subset of machine learning and enable computers to learn from data.

TPU vs CPU vs GPU: Key Differences

 

Processor	Description	Strengths
CPU (Central Processing Unit)	Introduced in the 1950s, it’s a general-purpose processor capable of handling a wide variety of tasks.	Versatile and sequential task processing. Modern CPUs can have 2 to 16 cores.
GPU (Graphics Processing Unit)	A specialized processor (also an ASIC) designed for parallel processing — executing many tasks at the same time.	Contains thousands of cores, ideal for complex computations like image rendering and deep learning.
TPU (Tensor Processing Unit)	Custom-designed by Google to run machine learning models with high efficiency.	Tailored for tensor operations and neural networks, offering optimized performance for AI workloads.