SSIC, which innovates within 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 powerful, 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", stated 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. With Cray's technology, we look forward to the progress and products our work will unlock."
"At Cray, we design our supercomputing systems for companies like Samsung that continually push the boundaries of research, design, and engineering to develop new products that improve people's lives", stated Fred Kohout, Cray's senior vice president of products and chief marketing officer. "We are honoured that Samsung has turned to Cray to provide the supercomputing resources it needs to bring new innovations to market."
The Cray CS-Storm systems provide customers with powerful, 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 leading-edge 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.