Webinar: Using NVIDIA-Based Distributed Processing to Speed Mission-Critical AI at the Edge

August 30, 2022

The need for evolving data center-caliber technologies architected to deliver higher performance and enable powerful centralized edge processing is growing exponentially. Greater amounts of data ingest from sensors must be analyzed in real-time to gain actionable insights for decision-making and competitive advantages.

For the first time in the market, there is an optimized network-attached rugged distributed GPU processing system purpose-built for challenging AI edge workloads. Join NVIDIA and Mercury to learn more about how they are:

Speeding low-latency, network-attached everything at the edge with disaggregated processing
Enabling GPU parallel computing resources via high-speed Ethernet networks without an x86 host
Pairing NVIDIA DPUs and GPUs for high-performance applications
Designing Rugged Distributed Processing (RDP) servers that reduce SWaP, cost and complexity of deploying GPU servers

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Article: Optimizing the Edge Through Distributed Disaggregation

Disaggregating processing is now enabling low-latency, network-attached everything at the edge with high-sp...

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White Paper: Massive Disaggregated Processing for Sensors at the Edge

Optimized networked-attached GPU distributed processing architecture delivers NVIDIA A100 GPU parallel comp...

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Webinar: Using NVIDIA-Based Distributed Processing to Speed Mission-Critical AI at the Edge

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