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Snap slashes data processing costs by 76% by switching to GPU-accelerated pipelines

By migrating over 10 petabytes of daily processed data to GPU infrastructure on Google Cloud, Snap optimized performance and achieved significant operating cost savings.

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Sources x.com

Snap, the company behind Snapchat, has announced impressive results after migrating its large-scale data processing infrastructure to GPUs.

Key Developments

Prudhvi Vatala, Head of Engineering Platforms at Snap, stated that his team successfully migrated the system processing over 10 petabytes of daily data to GPU-accelerated pipelines on Google Cloud. As a result, job execution costs plummeted by up to 76%, while the speed of running A/B tests at a scale of billions of users also saw significant improvements.

Why This Matters

This is a clear demonstration that GPUs are not only useful for AI training but are also highly effective for big data processing. For Vietnamese tech startups facing the challenge of rapidly growing data volumes, Snap's experience offers a valuable lesson on utilizing specialized hardware to both boost performance and optimize cloud budgets.