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.

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.

This case study describes how an organization ensured there was no transmitter interference with other onboard electronics.

Proven solutions for missile, sounding rocket, UAV, space vehicle, rotorcraft, and fast jet test applications.

For Canadian programs, Curtiss-Wright’s ability to design, develop, and manufacture technology on Canadian soil supports the Government of Canada’s Industrial Technological Benefits and Value Proposition (ITB/VP) Program.

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.