Optimizing the way in which machine learning algorithms are implemented in hardware will be a major differentiator for SoCs, especially for edge devices.
Antifuse-based OTP NVM is highly scalable, has the area efficiency to enable macros of megabit capacities, and offers low read power.
The basics of USB 3.2, how to implement it in an SoC, and how USB Type-C connectors and cables are used in USB 3.2 systems.
The proliferation of attacks against embedded systems is making designers realize that they need to do more to secure their products and ecosystems.
Exchange frameworks are emerging to make it easier for neural-network developers to swap between development environments.
Machine-learning strategies for embedded vision are evolving so quickly that designers need access to flexible, heterogenous processor architectures that can adapt as the algorithms evolve.
Designers need to understand how the architecture of electronic control units used to implement ADAS in vehicles is changing.
An evolution of the Ethernet standard enable time-sensitive networking with the predictable latencies and guaranteed bandwidth necessary for automotive applications.
Many car manufacturers are exploring the possibilities of autonomous vehicles. But what will it take to build sufficient AI performance into them to enable true autonomy?
Artificial intelligence and machine learning require the performance and flexibility offered by embedded FPGA (eFPGA) technology.
View All Sponsors