OSS to Host AI at the Edge Webinar with Leaders from NVIDIA and Marvell
One Stop Systems, Inc., a leader in specialized high-performance edge computing, will host a webinar on how to bring supercomputing performance to ‘data at the edge’ for AI applications with leaders from NVIDIA and Marvell.
The panel will be moderated by OSS chief sales and marketing officer, Jim Ison. He will be joined by Ying Yin Shih, director of product management at NVIDIA and Larry Wikelius, vice president, ecosystem and solutions at Marvell.
Topic: AI at the Edge: Bringing Supercomputing Performance to the Data
The webinar will discuss solving hard problems in defense, aerospace, autonomous vehicles, security, personalized medicine and more by leveraging massive NVIDIA enabled AI solutions designed for the unique size, power and rugged requirements of the edge.
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A new computing paradigm is emerging that puts computing and storage resources for AI and HPC workflows not in the datacenter but on the edge near the data source. Applications continue to emerge for this new paradigm in diverse areas, including autonomous vehicles, precision medicine, battlefield command and control, industrial automation, and media and entertainment.
The common elements of these solutions are high data rate acquisition, high-speed and low-latency storage, and efficient, high-performance compute analytics—all configured to meet the unique environmental conditions of edge deployments.
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This webinar will explain the challenges and solutions for meeting these requirements by describing real world use cases being developed and deployed today. OSS will present use cases of its edge-focused AI on the Fly® products currently deployed in intelligence, surveillance and reconnaissance (ISR), genomic analysis, location-based entertainment, and autonomous driving.
NVIDIA and Marvell will describe their collaboration to support NVIDIA CUDA® and CUDA-X software platform on the high performance, low power Arm® architecture with Marvell’s ThunderX2® server processor. The combination provides a powerful tool in the expanding set of solutions for edge-focused AI infrastructure. The panel will discuss how CUDA for Arm provides an effective AI on the Fly building block for edge-oriented solutions where high performance, memory bandwidth and low power are essential.
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