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Atipa Technologies Announces Procyon G-Series Platform Powered by NVIDIA AI Solutions

By ET Bureau - November 17, 2020 2 Mins Read

Atipa Technologies Announces Procyon G-Series Platform Powered by NVIDIA AI Solutions

Today, Atipa Technologies, a leading provider of high-performance computing and storage solutions, announced the launch of the Atipa Procyon G-Series deep learning and high-performance computing platform powered by the latest NVIDIA A100 Tensor Core GPU built on NVIDIA Ampere architecture, and leveraging AI containers, models and frameworks from the NVIDIA NGC catalog.

Data scientists and researchers require deep learning frameworks in order to transform  massive data sets into usable information that can be effectively utilized for scientific simulations. Installing and maintaining, these frameworks and dependencies require time and expertise that may not be easily available to researchers.

Atipa Procyon G-series servers allow users easy access to the NGC catalog for GPU-optimized applications for deep learning, machine learning, and high-performance computing (HPC). Supporting up to eight GPUs per server and offering flexible choices for GPU-to-GPU communication, fast NVMe flash storage, and low-latency, high-bandwidth NVIDIA Mellanox HDR 200Gb/s InfiniBand networking, the Atipa Procyon G-series family provides unprecedented performance and configurability. Single or dual AMD Epyc™ processors enable full PCIe Gen 4 support, doubling the bandwidth between GPUs and between GPUs and CPUs compared to the previous generation Atipa Procyon servers.

Read More: Is There Such a Thing as Too Much Cloud Flexibility?

“The ability to download containers with popular frameworks such as TensorFlow and Caffe, or high-performance computing applications such as Gromacs and LAMMPS, pre-installed with all necessary libraries and dependencies is an enormous time saver for IT staff,” says Bart Willems, Technology Director at Atipa Technologies. “By using NGC containers on Atipa Procyon G-series servers, scientists further benefit from continued updates and performance optimizations by NVIDIA GPU-optimization experts.”

“Time is everything for researchers, and getting to a solution depends on many factors: simulation time, but also time to build, install and optimize applications,” said Paresh Kharya, senior director of product management and marketing for Accelerated Computing at NVIDIA. “The Atipa servers with A100 GPUs built on NVIDIA Ampere architecture leverage NGC to enable scientists and researchers to more easily access the power of GPU acceleration to produce results.”


ET Bureau

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