Revving Up Efficiency: Leading Vehicle Inspection App Slashes Training Times by 46% with A100 GPUs for Faster Automotive AI
About the Client
The client leverages cutting-edge AI to revolutionize vehicle inspections. Their innovative application accurately extracts information from vehicles, fostering transparency and trust between car owners and service associates. The system then analyzes these images in under 3 minutes, generating a detailed report. This efficiency is valued by its users, with over 2,500 US dealers leveraging the application to complete millions of inspections annually.
Their Challenges
In the automotive industry, efficiency and accuracy are paramount. A leader in AI-powered vehicle inspection technology, the client faced limitations with their existing infrastructure that hindered their ability to deliver optimal performance:
Processing Bottleneck with P100 GPUs
While functional, the client's current P100 GPUs lacked the processing power to handle the increasing complexity and computational demands of their AI models. This resulted in slower analysis times, impacting workflow efficiency and potentially delaying vehicle inspections.
Limited Scalability for Future Growth
The P100 architecture presented a barrier to scaling the client's AI models for future advancements and tackling more intricate tasks. This could restrict their ability to address evolving needs within the automotive industry.
Maintaining Client
Satisfaction
Slower analysis times and limitations on model complexity could potentially hinder client satisfaction with their technology. Faster turnaround times and the ability to handle more complex inspections are crucial for maintaining a competitive edge.
The Solution
Optimized Environment Setup
A replica of the client's Python environment was established on Google Cloud, ensuring compatibility with the A100 architecture. Additionally, Searce ensured the installation of necessary libraries specifically designed to optimize development for A100 GPUs.
IMPACT
Faster Analysis & Performance
A100 GPUs enabled speedy processing, leading to quicker inspections and better model accuracy
IMPACT
Reduced Costs
Faster training times with A100 GPUs lower operational expenditures compared to scaling up with P100s
Codebase Refactoring for A100
The existing codebase underwent a thorough refactoring process. This involved updating the code to leverage the latest framework versions and libraries that are optimized to harness the power of A100 GPUs.
Advanced Model Optimization Techniques
Beyond the migration itself, Searce implemented advanced model optimization techniques to further enhance performance on A100 GPUs. These techniques included distributed training, which utilizes multiple GPUs for faster training, multi-worker data loaders for efficient data handling, and mixed precision training for memory optimization.
IMPACT
Improved Client Satisfaction
Faster turnaround times and the ability to handle complex tasks resulted in happier clients and new business opportunities
Success Story Highlights
Searce's AI solution for the client slashed training times by nearly half. Originally taking 70 minutes for 20 epochs, Searce reduced this to just 38 minutes using single-machine multi-GPU training, translating to a 46% improvement. Accuracy remained high throughout at 97%. These advancements empowered them to leverage A100 GPUs for faster analysis and model performance, & lower operational costs.
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