Nvidia open-source ML platform ‘turbocharges’ data science

Nvidia open-source ML platform ‘turbocharges’ data science

Technology News |
By Rich Pell

The RAPIDS open-source GPU-acceleration platform for data science and machine learning, says the company, enables even the largest companies to analyze massive amounts of data and make accurate business predictions at unprecedented speed. The platform is offered as providing data scientists a “giant” performance boost in addressing highly complex business challenges such as predicting credit card fraud, forecasting retail inventory, and understanding customer buying behavior.

“Data analytics and machine learning are the largest segments of the high-performance computing market that have not been accelerated — until now,” said Jensen Huang, founder and CEO of Nvidia, in his keynote address at the company’s GPU Technology Conference. “The world’s largest industries run algorithms written by machine learning on a sea of servers to sense complex patterns in their market and environment, and make fast, accurate predictions that directly impact their bottom line.”

“Building on CUDA and its global ecosystem, and working closely with the open-source community, we have created the RAPIDS GPU-acceleration platform,” he said. “It integrates seamlessly into the world’s most popular data science libraries and workflows to speed up machine learning. We are turbocharging machine learning like we have done with deep learning.”

The platform builds on popular open-source projects – including Apache Arrow, pandas, and scikit-learn – by adding GPU acceleration to the most popular Python data science toolchain. To bring additional machine learning libraries and capabilities to RAPIDS, Nvidia says it is collaborating with open-source ecosystem contributors. To facilitate broad adoption, the company is integrating RAPIDS into Apache Spark, the leading open-source framework for analytics and data science.

The platform offers a suite of open-source libraries for GPU-accelerated analytics and machine learning, with data visualization soon to follow. Nvidia lists a number of companies that are supporting RAPIDS, ranging from open-source ecosystem contributors such as Databricks and Anaconda, to tech giants like Hewlett Packard Enterprise, IBM, and Oracle. Walmart is listed as one of the platform’s early adopters.

Access to the RAPIDS open-source suite of libraries is immediately available. Containerized versions of RAPIDS will be available this week on the NVIDIA GPU Cloud container registry.


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