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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As I formed an advisory board consisting of former military personnel, I was touched by the comment by one advisory member that stated, “while I was in the service, I had 600 Marines under me. Five of these Marines did not come back, but technology available today could have saved all their lives if it was deployed. I have a lifelong mission to encourage the use of available technology to save the lives of warfighters.”
Edge computing is becoming increasingly important due to the rapid growth of the Internet of Things (IoT), and the need for real-time data processing and analysis. Edge computing involves processing and storing data at the edge of the network, closer to where it is generated, rather than in a centralized location.
At One Stop Systems Inc. (OSS), we are proud to offer high-performance solutions that help our clients tackle the most demanding computing workloads. That's why we are excited to talk about the NVIDIA H100 Tensor Core GPU, an incredibly powerful GPU designed to deliver exceptional performance for a wide range of use cases.
Monitoring computer systems is essential for maintaining the performance and reliability of a system. In today's digital age, the consequences of system failure or malfunction can be catastrophic for individuals and businesses alike. Monitoring tools such as Prometheus and Grafana can provide valuable insights into the health of a system, enabling users to identify potential issues before they become major problems.
Since the early stages of the 21st century, Peripheral Component Interconnect Express (PCIe) has established itself as the standard bus for workstation and server motherboards to interface with graphics cards, network cards, and many other categories of add-in cards. The throughput of full-length connections are heavily dependent on the generation of PCIe products being used, seen in the table below – and as the need for higher system performance in artificial intelligence and other computing applications intensifies, so does the demand for newer PCIe Gen5 products.
Artificial intelligence (AI) is a term that has become increasingly familiar to people around the world. It has the potential to revolutionize various industries and improve many aspects of our lives. However, not all AI is created equal. There are two types of AI: narrow and general. While general AI aims to create machines that can think and learn like humans, narrow AI focuses on specific tasks and is designed to perform them with precision and efficiency. In this blog, we will focus on narrow AI and explore its potential applications.
Artificial intelligence (AI) has found its way into many areas of our lives in recent years, and the technology is also being used more and more frequently in medicine. But what are the advantages of using artificial intelligence, what are the current and future application scenarios, and what challenges does medicine face on the hardware side in order to achieve them?
The Department of Defense (DoD) has a huge budget that companies want to tap into, but selling to the DoD is different from commercial sales. This article discusses the key differences and how to approach selling to the DoD.
The past two decades have seen an exponential growth in data generated because of increased digitization of the business processes, instrumentation of devices, and the need to capture, collect and process vast quantities of unstructured data such as video and images. This evolution has resulted in the development of new programming languages, new data storage architectures, and rapid advances in the infrastructure and chip architectures required to transform these new aggregated data sets into business insight and competitive advantage for businesses and governments.
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