GPU giant Nvidia has announced that its new open source GPU-acceleration platform called Rapids could transform the data analytics space with its ability to process huge amounts of data “to make accurate predictions at an unprecedented speed.”
Carly Page reported on GPU-based computing for The Inquirer:
Early benchmarks shown off by Nvidia, which ran Rapids using the XGBoost machine learning algorithm on an Nvidia DTX-2 system, shows a 50 times speed improvement compared to a CPU-only system. This, the company claims, will allow data scientists to reduce typical training times from days to hours, or from hours to minutes, depending on the size of their dataset.
Rapids has some big-name support at launch, ranging from the likes of as Anaconda, BlazingDB and Databricks to open source pioneers IBM, HPE and Oracle. “The compute world today requires powerful processing to handle complex workloads like data science and analytics – it’s a job for Nvidia GPUs,” swooned Clay Magouyrk, senior vice president of Software Development at Oracle Cloud Infrastructure.
“Rapids is accelerating the speed at which this processing and machine learning training can be done. We are excited to support this new suite of open-source software natively on Oracle Cloud Infrastructure and look forward to working with Nvidia to support Rapids across our platform, including the Oracle Data Science Cloud, to further accelerate our customers’ end-to-end data science workflows.
