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Oracle and NVIDIA Partner on Analytics, Machine Learning, and AI


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Oracle and NVIDIA have announced that Oracle is the first public cloud provider to support the NVIDIA HGX-2 platform on Oracle Cloud Infrastructure, helping to meet the needs of the next generation of analytics, machine learning and  artificial intelligence (AI). The companies are also announcing the general availability of support for GPU-accelerated deep learning and high performance computing (HPC) containers from the (NGC) container registry on Oracle Cloud Infrastructure.

The collaboration with Oracle will help fuel innovation across a wide range of industries, said Ian Buck, vice president and general manager of Accelerated Computing at NVIDIA.

As the world of computing continues to push the boundaries of what’s possible, we are providing our customers with the software, tools and cloud infrastructure needed to solve the most complex challenges,” said Clay Magouyrk, senior vice president, software development, Oracle Cloud Infrastructure. “Whether you are an engineer, data scientist, researcher, or developer, we are bringing the power of compute and cloud to your fingertips.

Rapid progress in AI and HPC has transformed entire industries while also demanding increases in complexity and compute power. According to NVIDIA, HGX-2 is designed for multi-precision computing to accelerate the most demanding applications by unleashing 2 petaflops of computing power and half a terabyte) of total GPU memory with 16 NVIDIA Tesla V100 Tensor Core GPUs interconnected with NVSwitch. Supporting HGX-2 on both Oracle Cloud Infrastructure bare-metal and virtual machine instances, Oracle and NVIDIA are helping customers solve the greatest AI and HPC challenges for the most complex workloads.

Oracle is also announcing support for the open source software which was just announced by NVIDIA for executing end-to-end data science training pipelines accelerated on NVIDIA GPUs. RAPIDS is now generally available on Oracle Cloud Infrastructure via . By accelerating data science pipelines by moving workflows onto the GPU, RAPIDS helps optimize machine learning training with more iterations for better model accuracy. Data scientists can utilize RAPIDS with easier integration and minimal code changes, enabling them to y accelerate the Python data science toolchain. With this new offering and support for NGC containers, Oracle and NVIDIA are allowing customers to deploy containerized applications and frameworks for HPC, data science, and AI and run them on Oracle Cloud Infrastructure.

Oracle Cloud Infrastructure is also working with NVIDIA to support RAPIDS across its platform, including the Oracle Data Science Cloud, to further accelerate customers’ end to-end data science workflows. RAPIDS software runs on the Oracle Cloud, allowing customers to support all their HPC, AI, and data science needs, while taking advantage of the portfolio of GPU instances available on Oracle Cloud Infrastructure.

For more information, go to http://cloud.oracle.com/iaas and http://nvidianews.nvidia.com

 


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