Engineering Computing News
Engineering Computing Resources
December 7, 2017
Samsung Electronics Co. Ltd. has purchased a Cray CS-Storm accelerated cluster supercomputer, according to Cray. The Samsung Strategy & Innovation Center (SSIC) procured the system for use in its research into artificial intelligence (AI) and deep learning workloads, including systems for connected cars and autonomous technologies.
SSIC, which focuses on multiple technology categories including digital health, IoT, data infrastructure and smart machines, purchased and completed the installation of the three-cabinet Cray CS-Storm 500NX system with NVIDIA Tesla Pascal P100 SXM2 GPU accelerators. The system will facilitate SSIC’s research with accelerator-optimized solutions for running artificial intelligence and deep learning applications at scale with very large, complex datasets.
“At Samsung, we believe the rapid growth of data has untold potential to improve the way we live,” says John Absmeier, vice president of Smart Machines, Samsung Strategy & Innovation Center and senior vice president, Autonomous/ADAS Strategic Business Unit, HARMAN. “But first, we need to understand the technology – leveraging artificial intelligence and deep learning – that provides insights into all that data. Cray’s system helps Samsung do that development, and they even use Samsung’s own solid state drives in their system, providing fast and secure memory access.”
The Cray CS-Storm systems provide accelerator-optimized solutions for running machine learning and deep learning applications at scale. The Cray CS-Storm 500NX system was delivered to Samsung as a fully integrated cluster supercomputer, with Samsung memory technologies including NVMe SSDs and 2666Mhz DDR4 RDIMMs, along with the Cray Programming Environment, and full cluster systems management. The Cray CS-Storm 500NX configuration scales up to eight NVIDIA Tesla Pascal P100 SXM2 GPUs using the NVIDIA NVLink to reduce latency and increase bandwidth between GPU-to-GPU communications, enabling larger models and faster results for AI and deep learning neural network training.
For more information, visit Cray.
Sources: Press materials received from the company.
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