# What is TPU? Definition & Technical Mechanics

> **Source:** [SPIDITS AI AI Glossary](https://spidits.com/ai-glossary)  
> **Category:** Hardware & Infrastructure  
> **Canonical Citation:** [https://spidits.com/ai-glossary/tpu](https://spidits.com/ai-glossary/tpu)

## Definition
A Tensor Processing Unit (TPU) is an application-specific integrated circuit (ASIC) custom-developed by Google specifically to accelerate machine learning workloads, specialized in high-performance matrix math operations.

## Architectural Mechanics & Deep Dive
A Tensor Processing Unit (TPU) is an application-specific integrated circuit (ASIC) developed by Google designed specifically to accelerate neural network workloads. NPUs and TPUs focus on high-speed matrix multiplications; TPUs power Google's cloud computing clusters, supporting large-scale model training and inference.

## Industry Applications & Real-World Use Cases
Massive scale model training, high-volume batch inference, and cloud model hosting.

## Frequently Asked Questions

### What is the difference between a GPU and a TPU?
GPUs are general-purpose processors designed for graphics and AI. TPUs are specialized ASICs engineered strictly for machine learning matrix multiplication.

### Can anyone use TPUs?
Yes, TPUs are accessible via Google Cloud Platform (GCP) or Google Colab environments.

## Related Terminology
- [gpu](https://spidits.com/ai-glossary/gpu)
- [deep-learning](https://spidits.com/ai-glossary/deep-learning)

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*From the SPIDITS AI Knowledge Base (336+ terms indexed). Explore full technical definitions: [https://spidits.com/ai-glossary](https://spidits.com/ai-glossary)*