GlaxoSmithKline (GSK) — a science-led global healthcare company — is using Kinetica GPU-accelerated analytics database to improve its management of its research and development (R&D) information platform.
Kinetica is enabling GSK's data science and analytics teams to leverage the power of their existing graphics processing units (GPUs), without needing to write custom code or use specialised software for each particular use case.
GSK is now able to open up a range of advanced and innovative use cases and communicate with their existing GPU cluster just like a typical relational database.
As the company can now communicate with their existing GPU cluster just like a typical relational database, users can interact with it using a traditional query language such as SQL.
Post implementation of the new GPU, GSK's data science and analytics teams can run workloads that require a more computationally-intensive environment for analysis in Kinetica.
Simultaneously, it can maintain the feel of communicating with a traditional relational environment.
GSK is satisfied with this investment as it is giving more returns than its previous investment in a GPU-accelerated cluster.
Previously they were using specialised and customised software to run chemical simulations on 125,000 GPU cores the cluster was not being taken advantage of for additional use cases.
GSK searched for a solution that allowed them to run a multitude of use cases on their GPU cores and finally selected Kinetica.
GPU-accelerated databases are in high demand in the pharmaceutical and healthcare industries. These can derive faster insights from vast volumes of streaming data and help researchers use algorithmic techniques with easy-to-use visual analytics tools to interactively run thousands of simulations across complex data sets.
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