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Definition of TPU (Tensor Processing Unit)
A TPU (Tensor Processing Unit) is a chip designed by Google and optimized specifically for calculations linked to neural networks. Unlike GPUs, which are versatile, TPUs are dedicated exclusively for ia calculationthus offering higher performance for certain tasks.
Why are TPUs crucial?
- Energy efficiency : a TPU consumes Up to 5 times less energy than a GPU For the same inference task.
- Increased performance for the training of AI models using Tensorflow.
- Native integration in Google Cloud AI For companies and startups.
Examples of use of TPUs
🔹 Google Bard (The Chatgpt competitor) works on V5E TPUs.
🔹 Deepmind uses TPUs for his research in biology and medicine.
TPU vs GPU: What difference?
| APPEARANCE | GPU (Ex. NVIDIA H100) | TPU (Ex. Google TPU V5E) |
|---|---|---|
| Use | Versatile (graphics, AI) | Specialized AI |
| Manufacturer | NVIDIA, AMD, Intel | |
| Power | High for AI but more generalist | Optimized for neural networks |
| Consumption | Higher | More economical |
| Cost | High ($ 30,000+ per unit) | Cheaper |
The future of TPUs
✅ Integration increased in Google Cloud AI.
✅ Potential to replace GPUs for certain AI tasks.
✅ Increasing adoption by companies to reduce inference costs.
