Microcontrollers are becoming a key platform for processing machine learning at the edge due to two significant changes. First, they now can include multiple cores, including some for high performance and others for low power, as well as other specialized processing elements such as neural network accelerators. Second, machine learning algorithms have been pruned to the point where inferencing no longer requires massive compute power and memory. Steve Tateosian, senior vice president for Infineon's IoT, Compute & Wireless Business Unit, talks with Semiconductor Engineering about the resources available in today's MCUs, including both off-chip and on-chip memory, low power, high performance, and embedded security.
6 сен 2024
