Ironwood: 7th Generation TPU

• 18 Apr 2025

Source: IE 

Why in News? 

Google has launched a new computer chip, called Ironwood. It is a 7th generation Tensor Processing Unit (TPU) designed to run Artificial Intelligence (AI) models.  

What are the Key Features of Google Ironwood TPU?  

• AI-Specific Design:  
  • Ironwood is optimized for "thinking models" like Large Language Models (LLMs) and Mixture of Experts (MoEs), enabling proactive AI that generates insights, not just data.  
  • Powerful Performance: Ironwood supports up to 9,216 chips per pod, delivering 42.5 Exaflops of compute, more than 24x the power of the world's largest supercomputer, El Capitan.  
  • Energy Efficiency: Ironwood delivers double the performance per watt compared to the previous generation, using advanced liquid cooling for power efficiency.  
  • Scalable AI Workloads: Ironwood is part of Google Cloud's Hypercomputer architecture, enabling the scaling of generative AI models and supporting the demands of advanced AI tasks. 

What are Processing Units? 

• About:  Processing units are hardware components that act as the brain of a computer. 
  • They carry out tasks similar to those of the human brain, such as reading, solving math problems, performing calculations, capturing images, or sending messages. 
• Types of Processing Units:  
  • CPU (Central Processing Unit) 
  • GPU (Graphics Processing Unit) 
  • TPU (Tensor Processing Unit) 

What is a Tensor Processing Unit (TPU)? 

• A Tensor Processing Unit (TPU) is a type of Application Specific Integrated Circuit (ASIC), Its purpose is to handle a narrow set of specific tasks. 
• TPUs were specifically developed to accelerate machine learning workloads and to handle AI-specific computational tasks, making them more highly specialized than both CPUs and GPUs. 
  • They run Google’s main AI services, such as Search, YouTube, and DeepMind’s language models. 
• They are highly efficient at handling large datasets and running complex neural networks, allowing for faster training of AI models compared to traditional processors.      

What is the Difference between CPU, GPU and TPU? 

Feature	CPU	GPU	TPU
Primary Function	General-purpose computing	Parallel processing, graphics rendering	Accelerating machine learning workloads
Processing Type	Sequential processing (can also include some parallelism in modern CPUs)	Parallel processing	Parallel processing (optimized for AI tasks)
Number of Cores	1 to 16 cores (can be more in advanced CPUs)	Thousands of cores	Specialized cores optimized for tensor operations
Performance for AI	Not optimized for AI	Good for AI tasks, especially for large datasets	Highly optimized for deep learning and neural networks
Efficiency	Versatile but less efficient for parallel tasks	Highly efficient for parallel tasks (e.g., deep learning training, large-scale data processing)	Extremely efficient for AI, especially neural network training
Real-World Applications	Personal computing, business applications, software development	Autonomous vehicles, facial recognition,  video processing, AI model training	Healthcare AI (e.g., diagnostics), autonomous systems, speech recognition, image recognition

 

UPSC Civil Services Examination Previous Year Question (PYQ) 

Prelims

Q. With the present state of development, Artificial Intelligence can effectively do which of the following? (2020)

1. Bring down electricity consumption in industrial units 
2. Create meaningful short stories and songs 
3. Disease diagnosis 
4. Text-to-Speech Conversion 
5. Wireless transmission of electrical energy 

Select the correct answer using the code given below: 

(a) 1, 2, 3 and 5 only 
(b) 1, 3 and 4 only 
(c) 2, 4 and 5 only 
(d) 1, 2, 3, 4 and 5 

Ans: (b)