Monks boosts processing speed by four times for real-time diffusion AI image generation using Amazon SageMaker and AWS Inferentia2

This article discusses how Monks, a digital brand experience company, used Amazon SageMaker asynchronous inference endpoints and AWS Inferentia2 chips to optimize the performance and cost-efficiency of their real-time diffusion AI image generation pipeline.

Specifically, the article covers:

• Challenges faced by Monks in maintaining consistent inference performance and cost management for their image generation processes
• How SageMaker asynchronous inference endpoints and AWS Inferentia2 chips addressed these challenges by enhancing processing speed and reducing costs
• The solution architecture, including components like endpoint creation, request handling, processing and output, and notifications
• Using custom Amazon CloudWatch metrics to create effective auto-scaling policies for the asynchronous inference endpoints
• Performance and cost benefits achieved by deploying their model on AWS Inferentia2 chips, including a 4x increase in processing speed and 60% cost reduction per image
• Conclusion and recommendations for using SageMaker deployment options and AWS Inferentia2 for generative AI use cases