Distributed deep learning from Horovod
The training introduces participants to the world of distributed deep learning model training using the Horovod framework. The program is designed to show how to effectively scale neural model training on computing clusters. During the intensive workshop, participants learn to implement distributed training algorithms, optimize performance and manage resources in a distributed environment. The class combines theory with practical exercises on real computing infrastructure.
Issues
The training program covers key aspects of distributed deep learning model training. Participants will learn about Horovod architecture, parallelization techniques, communication optimization, resource management, performance monitoring and operational best practices. Special emphasis is placed on the practical aspects of implementing and optimizing distributed training.
Benefits
- Implementing and optimizing distributed deep learning training
- They will gain knowledge of distributed systems architecture, parallelization techniques, communication optimization and resource management
- Methods for efficient training scaling, debugging techniques and best practices in distributed ML system development
Who is this training for?
Prerequisites
- Prior to training, participants should have hands-on experience in training deep learning models and basic knowledge of distributed systems
- Familiarity with Python and basic systems administration is also advisable
Training program
Distributed system architecture
- Integration with ML frameworks
Communication models
- MPI Basics
- Implementation of distributed training
- Parallelization strategies
- Synchronous and asynchronous SGD
- Optimization of communication
Ring-allreduce
- Performance optimization
Memory management
- Bandwidth and latency
- Performance profiling
Debugging
- Integration and implementation
- Integration with orchestration systems
- Monitoring of distributed training
Fault tolerance
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
Who is the Distributed deep learning from Horovod training for?
This training is designed for professionals looking to develop skills in distributed deep learning from horovod. Required level: intermediate.
How long is the Distributed deep learning from Horovod training?
The training lasts 1. Available in online or on-site format.
Will I receive a certificate?
Yes — every participant receives a completion certificate confirming acquired competencies. EITT holds ISO 9001 accreditation.
Can this training be conducted for a closed group?
Yes — we offer dedicated closed trainings for companies. We customize the program to your team's needs. Contact us for an individual quote.
Request a quote
Funding Options
Check funding options for your company
Development Services Database
Up to 80% funding for SMEs from EU funds
Check availabilityNational Training Fund
Up to 100% funding for employers
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Interested in this training?
Contact us - we'll prepare an offer tailored to your organization's needs.