Servers: The Right Compute
cancel
Showing results for 
Search instead for 
Did you mean: 

More freedom! New RAPIDS GPU-accelerated open source software available from NGC container registry

BillMannel

 

HPE_NVIDIA_RAPIDS_open source software_NGC_blog.jpgMore freedom is a beautiful thing! And it’s here now for data scientists: RAPIDS Open Source libraries for GPU-accelerated open software, available from the NGC container registry.

We’re NGC-Ready. Here’s what that means.

HPE is NGC-Ready with a NVIDIA program that expands the places where people can run AI and HPC applications. It allows users of powerful systems like HPE Apollo 6500 Gen10 systems with NVIDIA GPUs to deploy with confidence. HPE validated the HPE Apollo 6500 Gen10 system with GPUs to bring you the benefits of NGC for AI, machine learning, and HPC containers, in concert with our world-class hardware.  

To help you get the most out of your AI project, HPE will enable you to run GPU-accelerated software from the NGC container registry, including its expanded HPC and AI software library with new machine learning and analytics containers—and run with confidence on HPE Apollo 6500 Gen10 systems.

What is NGC?

The NGC container registry is a cloud-based catalog of GPU-accelerated software featuring ready-to-run containers for AI and HPC that are tuned, tested and optimized across the stack, taking full advantage of NVIDIA GPUs. These containers can be easily downloaded, helping you get the most from your hardware investment without worrying about difficult and time-consuming DIY software integration

The NGC container registry provides performance-engineered containers for the most popular AI and HPC software, including TensorFlow, PyTorch, NVIDIA TensorR, NAMD, GROMACS, ParaView, NVIDIA IndeX, NVIDIA Holodeck, and the newly released RAPIDS. The top deep learning framework containers are tuned monthly by NVIDIA engineers for maximum performance from NVIDIA GPUs.

What is HPE’s role?

HPE has already validated some NGC containers. These results, along with additional tests on other GPU-relevant based systems, can be found in the HPE Deep Learning Cookbook. These set of tools and recommendations is designed to help you choose the right technology and configuration for their deep learning tasks.

RAPIDS is here. Ready to accelerate your data science pipeline.

The RAPIDS suite of open source software libraries delivers the freedom to execute data science and analytics pipelines entirely on GPUs. Learn what this means for large-scale data analytics and machine learning—and why HPE is on board.

NVIDIA’s recent introduction of RAPIDS open-source software is welcome news for data scientists as they tackle problems that demand an increase in the scale of data as well as the computational power required to process it. 

It’s good news for business leaders too, as this accelerated open-source approach can enable even the largest companies to analyze massive amounts of data and make accurate business predictions at unprecedented speed.

What is RAPIDS?

Available now in a ready-to-run container from the NGC container registry, RAPIDS is a suite of open-source software libraries for executing end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA CUDA primitives for low-level compute optimization, but exposes GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces.

RAPIDS aims to accelerate the data science pipeline, including data loading, ETL, model training, and path to inference. It dramatically speeds up the data science pipeline by moving workflows onto the GPU. It also optimizes machine learning training with more iterations for better model accuracy. Additionally, hassle-free integration and minimal code changes, accelerate the Python data science tool chain.

The RAPIDS results? More productive, interactive, and exploratory workflows. Data scientists reap the benefits that come with a giant performance boost as they address highly complex business challenges, such as predicting credit card fraud, forecasting retail inventory, and understanding customer buying behavior.

What is HPE’s role?

HPE is among the leading technology companies, startups, and open-source community members who are already committed to and validated for RAPIDS. Our support reflects the growing industry-wide consensus about the importance of GPUs in data analytics. 

“HPE is committed to advancing the way customers live and work. Artificial intelligence, analytics and machine learning technology can play a critical role in uncovering insights that can help customers achieve breakthrough results and improve the world we live in. HPE is unique in the market in that we provide complete AI and data analytics solutions from strategic advisory to purpose-built GPU accelerator technology, operational support and a strong partner ecosystem to tailor the right solution for each customer. We are excited to partner with NVIDIA on RAPIDS to accelerate the application of data science and machine learning to help our customers drive faster and more insightful outcomes.”    – HPE CEO Antonio Neri describing the forward-looking nature of HPE’s partnership with NVIDIA and our support for the launch of RAPIDS

To demonstrate our commitment, HPE has validated the HPE Apollo 6500 Gen10 system and 8x 32GB SXM2 NVIDIA V100 GPUs connected by NVIDIA NVLink with RAPIDS resulting in up to greater than 6x data processing rate with 8 GPUs.* Increasing data processing time in training models is critical in AI. The faster your business can move from training models to inference, the faster you can begin unlocking insights from your data.HPE_NVIDIA RAPIDS_containers.jpgToday, HPE is ready to work with customers on end-to-end data science workflows with RAPIDS.

Read up on RAPIDS

More resources for you:

Learn more at Supercomputing 18

If you happen to be in Dallas on November 12-15, be sure to stop by the HPE booth #2429 at SC18 showcasing HPE Apollo 6500 Gen10 and RAPIDS. It’s a great opportunity to earn how HPE and NVIDIA can help you on your next AI project.

For additional info now, please reach out to your HPC/AI specialist or contact AI_MadeEasy@hpe.com and someone will be in touch with you.


Bill Mannel
VP & GM - HPC & AI Segment Solutions
Hewlett Packard Enterprise

twitter.gif @Bill_Mannel
linkedin.gif Bill-Mannel

0 Kudos
About the Author

BillMannel

As the Vice President and General Manager of HPC and AI Segment Solutions in the Data Center Infrastructure Group, I lead worldwide business and portfolio strategy and execution for the fastest growing market segments in HPE’s Data Center Infrastructure Group which includes the recent SGI acquisition and the HPE Apollo portfolio.