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.
READ MOREThe rugged edge computing landscape is becoming increasingly complex with new generations of technologies, such as the latest AI focused GPUs, releasing annually rather than every 2-3 years. Whether the end application is commercial or defense, rugged edge servers must not only deliver cutting-edge compute performance but also withstand extreme environmental conditions.
When the PCI-SIG formally added support for 675W add-in card devices in the PCI Express Card Electromechanical (CEM) specification in August 2023, NVIDIA’s most powerful CEM GPU, the NVIDIA H100 80GB had a maximum power consumption of 350W. While some devices were starting to push the limits of datacenter thermodynamics – high density systems of many 675W devices seemed like a distant reality. However, with power constraints uncapped and the need for higher performing GPUs skyrocketing, the industry quickly came out with devices taking full advantage of the new specification capability. NVIDIA quickly replaced the H100 80GB with the H100 NVL, increasing power density to 400W. While this small jump was manageable for existing installations, NVIDIA then dove all-in with the H200 NVL released in late 2024 at 600W. The rapid transition from 350W to 600W has put power and cooling technologies in the spotlight in a race to solve this next generation challenge.
The advent of technology has always brought about significant changes to various industries, and the transportation sector is no exception. Among the most transformative innovations in recent years is the development of autonomous vehicles, particularly trucks. The potential for autonomous trucks to revolutionize freight transport is immense, raising the fundamental question: will these technological advancements make human drivers obsolete? To explore this question, we must consider the current state of autonomous driving technology, the economic implications, and the societal impact of removing human drivers from the equation.
The integration of artificial intelligence (AI) into military operations has revolutionized battlefield strategies, decision-making, and operational efficiency. Among these advancements, AI inference nodes deployed directly on soldiers represents a cutting-edge innovation. These nodes, compact computational devices, enable real-time AI processing and analytics, empowering soldiers with enhanced situational awareness, decision support, and operational effectiveness. However, such technology also brings challenges, particularly in power management, size, and weight constraints. This blog delves into the advantages and disadvantages of implementing AI inference nodes on soldiers, focusing on these critical aspects.
The evolution of IT infrastructure spans several decades and is marked by significant advancements in computing technology, networking, storage, and management practices. Data Centers have historically relied on Converged or Hyper-Converged infrastructures when deploying their hardware which proved to limited in flexibility, efficiency, scalability, and support for the Artificial Intelligence / Machine Learning (AI/ML) modern workloads of today.
“Edge Computing” is a term which has been widely adopted by the tech sector. Dominant leaders in accelerated computing have designated “Edge” as one of their fastest-growing segments, with FY24 revenue projected to be nearly $100 billion. The boom in the market for Edge Computing has become so significant that it is increasingly common to see companies create their own edge-related spinoff terms such as ‘Rugged Edge’, ‘Edge AI’, ‘Extreme Edge’, and a whole slew of other new buzzwords.
The landscape of modern warfare is undergoing a profound transformation with the integration of cutting-edge technologies, and at the forefront of this evolution are autonomous military vehicles. Datalogging, a seemingly inconspicuous yet indispensable technology, plays a pivotal role in shaping the capabilities and effectiveness of these autonomous marvels. In this blog post, we delve into the critical role of datalogging in autonomous military vehicles and its impact on the future of defense strategies.
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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