TrustedCOTS™ and Enhanced Trusted COTS technologies use an OSA for embedding security, enabling customers to leverage S-SOTA technologies.

COTS products and open-architecture solutions for mission computing, signal processing, graphics, communication fabrics, system and sensing I/O, and data storage.

This white paper looks at whether Arm’s commercial success can translate to defense and aerospace markets in order to meet the highest DO-254 requirements and fill the Power Architecture void.

Tensor cores are indispensable for performing the types of calculations needed for artificial intelligence (AI) and machine learning. The role of AI and machine learning in defense applications is on the rise, making tensor cores critical for defense.

Like humans, machines learn from experience. They make observations from inputs of images, text, or other data, and then look for patterns. After the machine runs through the mathematical layers, it learns to make better decisions based on the examples it was given.

Which is better for machine learning applications, 2nd Generation Intel Xeon Scalable Processors or NVIDIA’s T4? A head-to-head comparison helps explain whether you should choose a CPU or a GPU for your high-performance machine learning solution.

This white paper describes how modern AI technology can benefit the warfighter as embedded solutions at the network edge are deployed for military and aerospace platforms. Edge computing brings data storage and computation closer to where it's needed.

This white paper reviews popular processor architectures to help you make an informed decision when defining your electronics payload.

This white paper discusses the terminology, applications, challenges, and technology enablers for machine learning, deep learning, and artificial intelligence (AI) in the embedded computing market.

This white paper will explore the technology behind the Xeon D’s flexibility and how it can solve a diverse range of military and aerospace challenges.

In this paper, we describe the problem of developing sensor fault detection within airborne instrumentation systems, and solutions based on machine-learning techniques.