In our new white paper, we discuss how the growing number of transportable AI applications, from autonomous driving to object identification in military aircraft, increases the need for users and data scientists to focus on overall AI system architecture design rather than individual innovations in a single hardware component or piece of software.
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| January News | ||
Role of PCIe Expansion in Advancing Transportable AI System Design The growing number of transportable AI applications, from autonomous driving to object identification in military aircraft, increases the need for users and data scientists to focus on overall AI system architecture design rather than individual innovations in a single hardware component or piece of software.Where a traditional multi-rack datacenter may be able to integrate the latest individual enhancement in AI framework, processing, networking, flash storage or GPU, an integrated embedded AI system in a mobile environment requires a complete system change to take advantage of these innovations. |
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Accelerate your AI workflow with the NEW GAS-Rugged Unprecedented compute density, performance and flexibility in the first 10 PetaOPS† AI system for rugged edge computing environments  OSS' GAS-R features the world's most advanced accelerator, the NVIDIA® A100 Tensor Core GPU, enabling AI on the Fly® customers to consolidate training, inference, and analytics into a unified, deployable AI solution at the edge.With available rack and flange mounting options, adaptable power subsystems and unheard-of performance in a modest 23" depth aluminum enclosure the GAS-R excels in demanding autonomous driving vehicle and airborne applications with true "Datacenter in the Sky" capability. †INT8 inference with sparsity |
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Trends in High Performance AI at the Edge that all Professionals Need to Know Preview our November 2020 webinar with guest speakers from NVIDIA, then register and watch the FULL webinar. |
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