Katie Rivera of One Stop Systems explores how rack-scale composable infrastructure can be utilized for mixed workload data centers.
To read the article, click here.
Last week, OSS unveiled the newest version of its rack-scale GPU Accelerator products, the GPUltima-CI (Composable Infrastructure) at the NVIDIA GPU Technology Conference (GTC 2018). GPUltima-CI allows mixed use datacenters to greatly increase GPU, networking and storage resource utilization compared to similar hyperconverged server solutions.
The GPUltima-CI power optimized rack configuration features up to 32 dual Intel Xeon Scalable Architechture compute nodes, 64 network adapters, 48 NVIDIA Volta GPUs and 32 NVMe drives on a 128Gb PCIe switched fabric allowing for a large number of composable server configurations per rack. Using one or many racks, the OSS solution contains the necessary resources to compose a wide variety of combinations of GPU, NIC and Storage resources required in today's mixed workload data center.
A long-haul truck cruises by you on Interstate 10 in west Texas. You get a brief wave from the driver who seems unfocused on the road ahead. It’s hot and the road is bumpy. You didn’t realize it but you just encountered an autonomous driving truck in development, testing out the latest version of its Artificial Intelligence algorithms. The truck is loaded with unseen video cameras, lidar, radar and infer-red sensors. As it travels along it is seeing its environment and its on-board computers are making the thousands of little decisions that keep it moving safely to its prescribed destination. The driver is a safety layer that will be removed in future iterations of the design.
Adoption of the latest HPC and AI technologies in autonomous vehicles is creating a surge in vehicle real-time data processing capabilities. The growth in number, speed and resolution of vehicle sensors and related compute performance in autonomous vehicles has in turn led to increased demand for high-capacity, high-throughput storage. Effective storage within autonomous vehicles must meet three primary criteria: throughput to match the capture and processing rates, a rapid data transfer workflow for offloading the captured data, and a rugged environmental design to operate in any autonomous vehicle conditions.
To read the full article click here.
Notable achievements in 2021: One Stop Systems won several programs to provide data-center-class AI hardware into rugged mobile edge environments without compromising performance such as in Mobile Datacenters and Autonomous Trucks. It also launched the high performance Rugged Compute Server for AI Transportable applications, Rigel.