At NVIDIA, we are driving change in data science, machine learning, and artificial intelligence. Some of the key trends that drive us are as follows: The rise of Python as the most-used language for data analyticsIncreased demand for highly usable distributed computingThe need for more computational powerOpen-source software becoming mainstream in industry At the intersection … Continued
This is the second post in a series that will discuss the results from an air pollution monitoring use case conducted during the COVID-19 pandemic, and share code snippets to port existing CPU workflows to RAPIDS on NVIDIA GPUs.
Over the past couple of years, NVIDIA and NASA have been working closely on accelerating data science workflows using RAPIDS and integrating these GPU-accelerated libraries with scientific use cases. In this blog, we’ll share some of the results from an atmospheric science use case, and code snippets to port existing CPU workflows to RAPIDS on … Continued
GTC Fall 2020 marked the second anniversary of the initial release of RAPIDS. Created out of the GPU Open Analytics Initiative (GoAi) aimed at making accelerated, end-to-end analytics on GPUs easy, RAPIDS has proven GPUs are performant, easy to use, and transformative to the future of data analytics. By thinking about the relationship between software … Continued
Data collected on a vast scale has fundamentally changed the way organizations do business, driving demand for teams to provide meaningful data science, machine learning, and deep learning-based business insights quickly. Data science leaders, plus the Dev Ops and IT teams supporting them, constantly look for ways to make their teams productive while optimizing their costs … Continued
At GTC Europe in Munich Germany, NVIDIA announced RAPIDS, a suite of open-source software libraries for executing end-to-end data science and analytics pipelines entirely on GPUs. RAPIDS aims to accelerate the entire data science pipeline including data loading, ETL, model training, and inference. This will enable more productive, interactive, and exploratory workflows. The RAPIDS libraries … Continued
Today’s data science problems demand a dramatic increase in the scale of data as well as the computational power required to process it. Unfortunately, the end of Moore’s law means that handling large data sizes in today’s data science ecosystem requires scaling out to many CPU nodes, which brings its own problems of communication bottlenecks, energy, and … Continued
Doctors diagnose someone with Cardiovascular disease every 43 seconds so finding new and better ways to speed the diagnosis of heart disease couldn’t be more important. In collaboration with Booz Allen Hamilton, Kaggle and the National Institutes of Health, NVIDIA is pleased to support the second annual Data Science Bowl competition. During the 90-day competition, teams … Continued
See how innovations are driving new data science capabilities, applications, and bridges to open source communities. Learn the latest breakthroughs in data manipulation, machine learning, spatial analysis, graph analytics, data visualization, and more.
Australia’s first Data Arena powered by by nine NVIDIA Quadro K6000, with 27,000 CUDA cores lets you literally see, hear and feel data sets through 3D visualization. A few software developers from the University of Technology Sydney built a 3D, 360-degree data visualization room to help researchers and data scientists intuitively explore huge and complex data … Continued
Attend live events in the time zone that works best for you, or browse an extensive catalog of on-demand content showcasing innovative uses of GPU technology. Here’s a preview of some of the data science sessions we’re working on for GTC.
When data scientists want or need unlimited experimentation for creativity and better models overall, The NVIDIA DSC is designed to make developers productive faster while providing simple access to common tools and frameworks to make data science development on workstations easier and more productive.
Kick off 2021 with a listen to the newest episode of RAPIDSFire: the Accelerated Data Science Podcast.
Learn from the world’s most advanced data science teams, here are some highlighted data science sessions planned for GTC.
The NVIDIA Deep Learning Institute released the Accelerated Data Science Teaching Kit, co-developed with Professor Polo Chau.
