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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Generative, Inferencing and Natural Language Processing (NLP) AI applications have all seen explosive growth (NVIDIA market cap growth 3200%) and rapid proliferation in the last two years across commercial market segments such as Automotive, Aerospace, Manufacturing, Transportation, Banking, and Entertainment. The commercial consumption of AI has quite directly driven the need for High Performance Compute (HPC) solutions, and, specifically HPC solutions that operate in some of the most extreme environments on earth. By comparison, DOD compute systems for air/ground platforms, while significantly ruggedized for austere environments, lack the compute power to employ such technological advancements in AI…or worse, lack the capability to counter AI threats employed by adversaries using commercially available SW/HW.
The rapid onset of AI is managing its ways into every facet of our lives. It is unlikely you can go a day, or even hour, without in some way connecting with, using, or hearing about AI. This is especially true in Edge Processing markets where AI is integrated in vehicles and platforms in the environments we work and play in.
HPC systems are characterized by their high-speed processing power, high-performance networks, and large-memory capacity, generating the capability to perform massive amounts of parallel processing. When a standard desktop with a 3 GHz processor can perform around 3 billion calculations per second, an average HPC system can perform quadrillions of calculations per second. This means HPC systems perform extreme amounts of calculations in seconds, whereas a regular processor would take weeks or even months to complete the same task, thanks to their technology.
In my last blog post, What is the Workhorse Advancing HPC at the Edge?, I highlighted how enterprise applications requiring the highest end compute for their AI workloads at the Edge are leveraging data-center grade NVIDIA GPUs to get even greater performance. Processing and storing data closer to where the action takes place means a decision can be made more quickly, producing reduced latency, improved security, greater reliability, and much higher performance. In this blog, I’ll be covering the transition from using big power-hungry GPUs to smaller form factor electronic control units, better known as ECUs, at the very edge.
In the ever-evolving landscape of modern warfare, the United States Department of Defense (DoD) is at the forefront of developing advanced capabilities to maintain superiority on the battlefield. The Joint All-Domain Command and Control (JADC2) initiative has emerged as a critical framework for enabling real-time data sharing, decision-making, and operational coordination across all military branches and domains. One Stop Systems (OSS), a leading provider of high-performance computing solutions, has positioned itself as a key player in supporting JADC2 applications with their innovative and powerful hardware offerings.
The integration of Artificial Intelligence (AI) into warfare has revolutionized the technological landscape of modern military operations. AI-driven systems are capable of autonomously processing data, making intelligent decisions, and executing complex tasks with precision. In this blog article, we provide a comprehensive overview of the current capabilities of AI in warfare, explore future possibilities, and examine the challenges faced by the underlying hardware.
In today's ever-changing business landscape, one thing remains constant: the need to embrace change. I am referring to the broader concept of CHANGE itself. The world is continuously evolving, presenting both challenges and opportunities for businesses to stay relevant and engage with their customers. In this blog post, I will argue that the ability to swiftly adapt to new challenges is a significant competitive advantage for any company - a concept I like to call "quick to change."
When trying to explain what exactly One Stop Systems (OSS) does, it is easy to state, we repackage enterprise level components so they can be placed at the very edge. Seems easy enough, right? Simply take the components and design a rugged frame around them and boom! Instant success! From a 50,000-foot view, that is a simple way to explain it. The following article will go into more detail to explain a few things on how OSS differentiates itself from its competitors and why you should choose One Stop Systems for your next edge application project where you need performance without compromise!
As the field of artificial intelligence (AI) evolves, so does the hardware required to support AI applications. In particular, the demand for AI-rugged edge computing has never been higher.
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