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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A June 4, 2020 congressional report, “Intelligence, Surveillance, and Reconnaissance Design for Great Power Competition”, reinforced the importance of the United States’ military continuing to develop ISR (intelligence, surveillance and reconnaissance) capabilities as threats grow around the world. The report states that the goal is to “make rapid sense of that data; securely deliver that data to weapons, weapon systems, and commanders; and possess a workforce that can execute its mission in competition and combat, at a pace greater than the enemy.”
Here at One Stop Systems, we continually strive to learn from our customers and employees in order to be better than the day before! What better way than to partner with our community and students in our home of San Diego? We hosted our 2nd annual OSS Summer Internship with students from California State San Marcos/Fullerton, UC San Diego, and the SDSU campuses!
Most of us are familiar with or have at least heard the term ‘Edge’ or ‘Edge Computing’ when discussing new high-performance computing (HPC) technologies around the Internet of Things (IoT), Cloud Computing, Autonomous Vehicles, etc. How many of us can explain the different levels of performance between PCIe and 5G, in relation to edge computing? Moreover, why is it important when discussing (HPC) at the edge? In this post, we’ll take an in-depth look at the increasing need for greater performance at the edge and what HPC applications benefit from PCIe vs. 5G.
On June 8th 2022, the DOD’s chief information officer, John B. Sherman, held a fireside chat with Craig Martell, DOD's chief digital and artificial intelligence officer, at the DOD Digital and AI Symposium as reported by the DOD News. The article stresses the importance of digital transformation and artificial intelligence in enabling warfighters to maintain a battlefield advantage, even as China and Russia develop their own AI for military purposes.
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.
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