Data Platform > Graphics Processing Unit (GPU) Database Service
Graphics Processing Unit (GPU) Database Service
Overview
To take advantage of GPUs for such operations requires ground up development of the database. GPUs require specific programming, and operations need to be processed differently to take maximum advantage of its threading model. A modern analytics database holds data in a columnar store, optimized for feeding the GPU compute capability as fast as possible
Objective
- Customer can see complex queries returned in milliseconds even as the dataset grows and more nodes are added
- more customers are trying to solve for challenges where leading analytical databases can’t keep up with data ingest
Objective
- Customer can see complex queries returned in milliseconds even as the dataset grows and more nodes are added
- more customers are trying to solve for challenges where leading analytical databases can’t keep up with data ingest
Benefits
- Aggregations, sorts, and grouping operations are workload intensive for a CPU, but can be effectively parallelized on a GPU
- To get very fast result to calculate sophisticated formula
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