Computer server redundancy, including backup power supplies, RAID storage devices and applications that automatically fail-over, keeps critical systems up and running longer than non-redundant systems. Similarly, effective system monitoring can provide early warning of failures and allow system managers to remotely manage these systems, further improving application uptime. While the concepts of computer system redundancy and system management are well-established in all levels of computing, from the personal computer to the largest hyperscale datacenters, the unique challenges of placing datacenter-class computing elements performing AI applications in mobile edge environments, like aircraft, ships, and land vehicles, brings unique challenges to system redundancy and management.
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Artificial intelligence and machine learning in edge computing require testing data sets to provide accuracy and efficiency. How can this be done? Processing data sets and information through a model to make sure it achieves its intended purpose is done through a process known as model validation.
Between climate change and feeding the world: The world's farmers take on the vital task of supplying food to the world's ever-growing population. In this context, they face daily challenges such as the effects of climate change, rising commodity prices, or improving animal welfare, while they have to make their own production sustainable.
In this video, Braden Cooper, Product Marketing Manager at OSS, does a quick walkthrough of the OSS PCIe Gen 4 3U Short Depth Server (both AMD and Intel versions). The SDS has configurable motherboard options in a feature packed rugged server platform for GPU or FPGA accelerated computing, U.2/U.3 NVMe storage, and PCIe Gen 4 expansion.
While most AI workflows occur in the controlled environment of datacenters where servers have the HPC resources the applications need, many current AI applications require some or all the AI workflow steps to be performed out in the field, in harsh environmental conditions. Until now, companies with applications on the ‘edge’ have had to rely on low-performance hardware or deal with the latency of uploading data to the cloud; rugged edge-computing devices, like industrial PCs and IOT devices, are able to withstand the extreme environmental factors of harsh environments, but they do not come close to offering the same computational performance of servers in a datacenter. Because of this, AI applications on the ‘edge’ have had to compromise on performance, but not anymore!
Tires screeching to a halt, your car’s edge computer has predicted a collision warning and acted according to its scripted protocol without communication to a network. Edge computers of all sizes are taking the power of the data center and access of the cloud into environments where sensors and/or cameras are located.
One Stop Systems’ strategic focus is on artificial intelligence (AI) Transportables, a term self-defined by OSS to mean anything that moves or is transportable that requires the latest in technology, at the edge, operating in a harsh environment. Basically, the capabilities of the highest performance data center in the field. Though this definition incorporates a myriad of applications, one industry of focus is the use of such capabilities in autonomous or self-driving, long-haul trucks.
The words “Artificial Intelligence” may conjure up many images of science fiction books and movies. There may be many assumptions and misconceptions of how artificial intelligence is used, but artificial intelligence (AI) is predominantly used in the business world for both commercial and government applications.
The OpenVPX standards occupy a special place in deployed military compute platforms. Designed as a successor to VME64, the OpenVPX (ANSI 65) and related standards such as SOSA have offered the opportunity to package COTS systems that meet the challenging environmental and electrical requirements of military vehicles across all services. AI Transportable systems incorporate GPUs and switched fabrics that were not envisioned by the existing standard and threaten to force significant new investment in product development before deployment of next generation systems such as C4ISR.
In this video, Michael Bradley does a tour of the OSS booth at AUVSI XPONENTIAL 2022 in Orlando, FL from April 26-28. Michael discusses the products we showcased at XPONENTIAL and how they provide solutions for Edge AI for Autonomous Vehicles. OSS AI Transportable products can provide solutions for GPU acceleration, FPGA data ingest, and NVMe storage.
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