Google Cloud AI Training in Bangalore  Google Cloud AI Training
                     TPUS IN GOOGLE 
AccelCerLatOingU ADI and ML 
Performance
WHAT ARE 
Title: Understanding TTePnsoUr PSro?cessing Units (TPUs)
Content:
• TPUs are custom-developed AI accelerators by Google.
• Optimized specifically for tensor operations in 
machine learning.
• Designed to handle operations used in neural 
networks (e.g., matrix multiplication).
• First launched in 2016 and continuously evolving (v2, 
v3, v4).
Visuals: Diagram showing TPU chip next to CPU and GPU 
chips.
TPU EVOLUTION
Title: TPU Hardware Evolution (v1 to v4)
Content:
• TPU v1: Designed for inference (2016).
• TPU v2 & v3: Added training support, larger memory.
• TPU v4: Doubled performance per watt, 4x faster 
interconnects.
• TPU Pods: Supercomputing clusters with hundreds of 
TPUs.
Visuals: Timeline with performance and architecture 
improvements.
ARCHITECTURE OF GOOGLE CLOUD 
• Title: How TPUs WorkT inP tUhSe Cloud
• Content:
• TPUs are offered as standalone or in Pods.
• Each Pod is a supercomputer with high-speed 
interconnect.
• Supports up to 275 TFLOPS (per core).
• Tight integration with Google Cloud AI services.
• Visuals: Diagram of TPU core, board, and Pod 
layout.
REAL-WORLD 
Title: Real-WoArldP UPseL CaIsCesA foTr ITOPUNs S
Content:
• NLP: Training models like BERT, T5, PaLM.
• Vision: Object detection, image classification.
• Healthcare: Genomic analysis, diagnostics.
• Science: Protein folding, climate modeling.
Visuals: Icons or images for healthcare, NLP, vision, 
etc.
BENEFITS OF CLOUD 
Title: Why Choose TPUsT inP GoUogSle Cloud
Content:
• Speed: Fast training and inference.
• Scalability: Run on a few or hundreds of TPUs.
• Cost-effective: Pay-per-use pricing.
• Ecosystem: Integrated with TensorFlow, JAX, PyTorch.
• Fully Managed: No hardware overhead.
Visuals: Benefits shown with checkmarks and icons.
HOW TO GET 
Title: GettinSg STtaArteRd wTithE TDPUsContent:
1.Sign in to Google Cloud Platform.
2.Launch a TPU node via Cloud Console or 
Terraform.
3.Use pre-configured Jupyter notebooks.
4.Monitor with Vertex AI and Cloud 
Monitoring.
5.Train models with TensorFlow or JAX.
Visuals: Screenshot of TPU setup screen or 
code snippet.
SUMMARY
• Title: Recap & Where to Learn More
• Content:
• TPUs = High-performance AI accelerators.
• Ideal for ML workloads at scale.
• Integrated, scalable, and cost-efficient in 
Google Cloud.
• Explore more:
• cloud.google.com/tpu
• tensorflow.org
• jax.readthedocs.io
• Visuals: Logos + QR code to Google Cloud 
TPU docs.
CONCLUSION
For More Information About 
Google Cloud AI
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Hyderabad-16
  Ph. No: +91-998997107
    Visit: www.visualpath.in
     E-Mail: [email protected]
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