See how RAPIDS and the open source ecosystem are advancing data science. In this session, we will explore RAPIDS, the NEW open source data science platform from NVIDIA. Come learn how to get started leveraging these open-source libraries for faster performance and easier development on GPUs. See the latest engineering work and new release features, including, benchmarks, roadmaps, and demos. Finally, hear how customers are leveraging RAPIDS in production, benefiting from early adoption, and outperforming CPU equivalents.
The next big step in data science combines the ease of use of common Python APIs, but with the power and scalability of GPU compute. The RAPIDS project is the first step in giving data scientists the ability to use familiar APIs and abstractions for data science while taking advantage of GPU accelerated hardware commonly found in HPC centers. This session discusses RAPIDS, how to get started, and our roadmap for accelerating more of the data science ecosystem.
Learn how RAPIDS and the open source ecosystem are advancing data science. In this session, we will explore RAPIDS, the NEW open source data science platform from NVIDIA. Deep dive into the RAPIDS platform and learn how to get started leveraging the open-source libraries for easier development and enhanced performance data science on GPUs. See the latest engineering work, including benchmarks and demos. Finally, see how customers are benefiting from early primitives and outperforming CPU equivalents.
In this session, we will explore the latest work, showcase benchmarks, and provide demos of the GPU Open Analytics Initiative (GoAi), a collection of open-source libraries, frameworks, and APIs established to standardize GPU analytics to allow for easier development and enhanced performance for GPU-accelerated analytics technologies. Numerous Fortune 500 customers experience latency and performance issues in their data pipeline. Big data frameworks and solutions tried to address this problem, but the cost to scale to the volume and velocity of current needs has proven to be prohibitively expensive. GoAi is addressing these challenges with a vision is to create an end-to-end GPU-accelerated data pipeline that will smooth onboarding ramp for enterprises to explore and integrate AI into their core data driven decision making processes. The session will also provide examples of how customers are benefiting from early primitives and outperforming CPU equivalents.