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GTC ON-DEMAND

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Abstract:
At Uber, real-time analytics plays a critical role in gaining business insights and operational efficiency. It also enables us to make real-time data-driven decisions to improve user experiences on our transportation platform. GPU technology has advanced significantly over the years, making it a perfect fit for large-scale computation and data processing in parallel. We'll describe why we leverage GPUs to solve the real-time analytics problem at Uber and how we designed our system to fully utilize the GPU's parallelization power and minimize its drawbacks. We will also share learnings in GPU programming during the development of AresDB.
At Uber, real-time analytics plays a critical role in gaining business insights and operational efficiency. It also enables us to make real-time data-driven decisions to improve user experiences on our transportation platform. GPU technology has advanced significantly over the years, making it a perfect fit for large-scale computation and data processing in parallel. We'll describe why we leverage GPUs to solve the real-time analytics problem at Uber and how we designed our system to fully utilize the GPU's parallelization power and minimize its drawbacks. We will also share learnings in GPU programming during the development of AresDB.  Back
 
Topics:
Accelerated Data Science, Performance Optimization
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S91021
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