Efficient execution is key to real-time mission-critical operating systems software, yet new demands are emerging such as safety-critical operations for avionics and other life-critical applications.

Ivan Straznicky talks about the challenges of keeping rugged computer systems designed for military programs cool under harsh conditions as they grow more powerful and more complex.

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.

With faster processors, more functions, and higher bandwidth than ever before, today’s avionics are pushing the cooling technology envelope to the breaking point – and beyond.

The magic of tensors comes from their special transformational properties that enable them to describe the same physics in all reference frames.

Until recently, the use of moving liquid to remove excess heat from embedded computing processors was considered an expensive and unreliable luxury, but escalating demand and maturing technologies finally are putting this technology within reach.

This column will focus on frameworks that work with NVIDIA’s TensorRT, a tool for deploying high-­performance deep neural networks.

Thanks to parallel advancements in battery technology and autonomous vehicles resulting from Tesla and other pioneering electric automobile manufacturers, we are rapidly approaching the era of the unmanned flying taxi.