This white paper examines how building a system with a dissimilar redundant architecture can help overcome the challenges of meeting DO-254/178 DAL A requirements.

The goal of reducing the cost of equipping Army vehicles with new capabilities, while adding increasing interoperability and flexibility of operation, can be accomplished through the use of a Modular Open Systems Approach (MOSA), a technical and business strategy for designing an affordable and adaptable system.

This white paper examines the key challenges multi-core processors present in safety-certifiable systems, and the traditional and newer, more effective techniques for alleviating them to ensure MCP-based systems will safely perform their intended functions.

Building connected and workable communications in remote environments presents unique challenges, but the right technology can keep users connected in even contested and harsh environments.

This paper aims to put MOSA (Modular Open Systems Approach) into perspective and enable you, whether a defense contractor, a decision-maker at the DoD, or a public policymaker, to put the increasingly relevant MOSA to use better.

The military and aerospace market maintains an insatiable appetite for smaller, lighter, and cheaper. Recent technological breakthroughs in SWaP-C reduction have yielded the introduction of USFF mission computer and networking systems.

This essential guide describes MOSA's significance for defense technology and the roles standards like SOSA, CMFF, CMOSS, VICTORY, GVA, and FACE play.

This white paper was presented at the 2021 NDIA Ground Vehicle Systems Engineering and Technology Symposium, Vehicle Electronics Architectures Technical Session, August 10-12, 2021.

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.

This white paper looks at how using complementary PNT technologies that leverage proven and trusted techniques to arrive at an A-PNT truth can protect personnel and equipment in the field.

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.