GPU Databases

GPU databases

GPU accelerated databases are an emerging technology which can provide high-performance computing by parallelising tasks in a single machine (multi-tasking). Initially, GPUs (Graphical Processing Units) were used mainly for rendering graphics, images and videos, but their power to support big data processing was soon realised and applied in relational or non-relational databases.

Applications

  • Analytical workload 
  • Machine learning (ML) /data science
  • Graph processing
  • Spatial (location) data processing
  • Scientific workloads
  • Real-time data exploration

Benefits

  • Analytical efficiency
  • Speedy queries and scalable performance
  • Good visualisation capabilities
  • Easier IT management

Considerations

  • Cost-effectiveness 
  • Only workloads that are similar and can be split into parallel tasks can take advantage of GPUs

Our offerings

Feasibility Recommendations for a GPU Database

  • Verify feasibility of GPU database for a use case (based on data and cost)

Proof of Concepts (PoCs)

  • Verify feasibility of GPU database for a use case (based on data and cost)
  • Recommend a GPU database (on-cloud or on-premise)
  • Implement use case, benchmark performance and determine SLAs

Technologies

A GPU data warehouse

A graph processing GPU powered database

GPU database to query and visualize Big Data

Distributed, in-memory database using GPUs

Previously, PG Strom - an extension module of PostGreSQL on GPU

GPU database and analytics platform

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