AI BriefingSnap Boosts Snapchat A/B Testing Performance with Open Data-Processing Acceleration Library
Key point
Snap adopted NVIDIA cuDF to speed up data processing for Apache Spark-based A/B testing by 4x and cut costs by 76%.
Details
Snapchat runs thousands of experiments every month, processing over 10PB of data with Apache Spark for 3 hours every morning. To handle this, the company adopted NVIDIA cuDF, converting its existing CPU-based workflow into an NVIDIA GPU-accelerated approach.
Through this transition, Snap improved data processing speed by 4x with the same number of machines, and achieved a 76% reduction in daily costs compared to CPU on Google Kubernetes Engine.
In particular, by optimizing Google Cloud's G2 VM and NVIDIA L4 GPU, Snap was able to handle its target experiment scale with just 2,100 GPUs, instead of the originally projected 5,500 GPUs. Snap plans to expand this acceleration technology to a broader range of production workloads going forward.
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