Technologies / Artificial Intelligence

TPU programming - creating neural network applications on Tensor Processing Units

The training focuses on the practical use of Tensor Processing Units (TPUs) in the implementation of neural networks. The workshop program covers the specifics of programming on TPUs, performance optimization and implementation best practices. Participants will learn techniques for effective use of TPUs in deep learning projects through practical exercises. The class is conducted as an intensive workshop with real implementation examples.

Issues

TPU architecture and specifics
Tensor programming
Performance optimization
Memory management
Profiling and debugging
Parallel processing
Deployment on TPU
Scaling up solutions
Performance monitoring
Troubleshooting
Integration with AI frameworks
Optimization of calculation costs

Benefits

Upon completion of the training, the participant will be able to effectively use TPU in deep learning projects
He/she will gain the ability to optimize code for specific TPU architecture
Will be able to effectively manage computational resources in AI projects
Will master debugging and performance profiling techniques on TPU
Will learn to deploy and scale solutions using TPUs in a production environment
Will gain hands-on experience in programming deep learning models on TPUs
Will learn methods for monitoring and optimizing TPU resource utilization
Will be able to select appropriate processing strategies for different types of models

Who is this training for?

Deep learning engineers working with large models

Artificial intelligence programmers

AI performance optimization specialists

Architects of machine learning solutions

Developers of learning systems

Deep learning researchers

MLOps engineers

High volume data processing specialists

Prerequisites

Practical knowledge of deep learning
Experience in the implementation of neural networks
Knowledge of machine learning frameworks
Basic knowledge of systems architecture

Training program

Comparison with GPU and CPU
TPU development environment
Setting up and preparing the environment
Programming on the TPU
Programming model for TPU
Optimization of tensor calculations

Debugging techniques
Performance optimization

Data flow optimization
Parallel processing strategies
Monitoring of resources
Implementation and maintenance
Deployment of models on TPU

Production monitoring
Troubleshooting

Delivery Methods

Online

Convenience of participating from anywhere
Interactive live sessions with trainer
Materials available for 30 days
No travel costs

On-site

Direct contact with trainer and group
Intensive hands-on workshops
Networking with other participants
Full focus on learning

Frequently asked questions

What are the prerequisites for this training?

For TPU programming - creating neural network applications on Tensor Processing Units we recommend: Practical knowledge of deep learning; Experience in the implementation of neural networks; Knowledge of machine learning frameworks.

What is the format and duration of this training?

The training lasts 1 day and is available in online and on-site format. Sessions run from 9:00 AM to 4:00 PM. We can also customize the schedule to fit your team's needs.

Who is this training designed for?

This training is designed for: Deep learning engineers working with large models; Artificial intelligence programmers; AI performance optimization specialists.