Accelerating AI Workloads with AWS Graviton

Business Problem

SuperTrainer, a leading AI-powered fitness and coaching platform, needed high-performance computing capabilities for processing real-time analytics, AI-driven workout recommendations, and user engagement insights. Their existing infrastructure was struggling with performance bottlenecks and high operational costs due to increasing demand for AI computations.

Offered Solution

To optimize compute performance and reduce costs, we implemented AWS Graviton-powered EC2 instances tailored for AI workloads:

Migrated workloads to Graviton3-based EC2 C7g instances for enhanced AI model processing.

Optimized TensorFlow and PyTorch AI models to leverage ARM64 architecture for faster inference times.

Integrated AWS Lambda and Fargate with Graviton to handle background data processing and API responses.

Reduced compute costs by 40% through the efficient utilization of AWS Graviton and Spot Instances.

Success Criteria

AI inference times improved by 25%, enabling faster workout recommendations.

Compute costs reduced by 40% compared to traditional x86 instances.

Increased application stability and scalability to support more users without latency issues.

Lessons Learned

AI workloads can significantly benefit from ARM-optimized libraries.

AWS Graviton delivers faster, more efficient compute processing at lower costs.

Migrating AI models to Graviton requires thorough performance testing and optimization.

Team IHA INC is a leading Business Solution Provider. Developing customized AWS applications and our algorithms work to help businesses grow customers.

SuperTrainer – Accelerating AI Workloads with AWS Graviton

Business Problem

Offered Solution

Success Criteria

Lessons Learned

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