Efficient training of AI models is critical for performance, scalability, and cost-effectiveness. This workshop will provide participants with practical knowledge on optimizing model training, leveraging advanced techniques such as mixed precision and distributed computing, and profiling workflows to maximize efficiency. Attendees will gain actionable insights to improve performance while reducing resource consumption in real-world AI workloads.
This workshop is ideal for:
Machine Learning Engineers: Looking to accelerate training and optimize memory usage.
Data Scientists: Interested in improving model performance and resource efficiency.
AI/Deep Learning Researchers: Seeking strategies for scaling models across multiple devices.
IT and Infrastructure Teams: Responsible for deploying and maintaining high-performance training environments.
Mixed Precision Training: Understand how to use FP16 and BF16 to speed up training without losing accuracy.
Distributed Computing: Learn strategies for scaling training across GPUs and multi-node clusters.
Profiling Techniques: Identify performance bottlenecks and optimize memory and compute usage.
Cost and Time Efficiency: Reduce resource consumption while maintaining or improving model performance.
Real-World Applications: Explore case studies demonstrating optimization in production AI workloads.
Introduction to Training Optimization Techniques
– Overview of computational challenges in AI training
– Key concepts in precision, parallelism, and profiling
Mixed Precision Training
– Benefits of FP16 and BF16 in deep learning
– Implementation strategies in popular AI frameworks
Distributed Computing for Scalable Training
– Multi-GPU and multi-node setup
– Synchronization, gradient aggregation, and optimization techniques
Profiling and Performance Analysis
– Identifying bottlenecks in model training
– Tools and best practices for memory and compute optimization
Hands-On Lab and Use Cases
– Applying mixed precision and distributed training on sample models
– Profiling exercises to optimize real-world workloads
– Addressing participant-specific challenges
– Collaborative discussion of optimization strategies
Expert Insights: Learn from AI specialists with real-world optimization experience.
Practical Skills: Gain hands-on experience applying advanced training techniques.
Performance Improvements: Learn methods to enhance model efficiency and reduce costs.
Strategic Frameworks: Receive actionable guidance for scaling AI workloads.
Networking Opportunities: Connect with peers and industry experts for ongoing learning.
Elevate your AI model training capabilities and maximize performance and efficiency. Join us for this advanced workshop!
Let’s connect and build innovative software solutions to unlock new revenue-earning opportunities for your venture
We would love to hear from you
5th Floor, DLF Two Horizon Centre, DLF Phase 5, Gurugram, HR 122002
