NXP Semiconductors has released the new MCX portfolio of microcontrollers, created to advance innovation in smart homes, smart factories, smart cities and emerging industrial and IoT edge applications. The portfolio comprises four series of devices constructed on a common platform and supported by the widely adopted MCUXpresso suite of development tools and software. This combined offering enables developers to maximise software reuse over the portfolio to speed development. The portfolio also offers the first instantiation of its new, specialised neural processing unit for accelerating inference at the edge, providing up to 30x faster machine learning throughput than a CPU core alone.
Driven by the proliferation of edge devices, the MCU has developed dramatically over the last few decades. While they are at the heart of many of today's edge applications, the next generation of intelligent applications will need a new class of MCUs that enables developers to steer a complex landscape of power, performance and security necessities, as well as connectivity options, while balancing total system cost and energy efficiency. Constructed on a common foundation of core technologies and supported by a unified software suite for maximal software reuse, the portfolio will allow the flexibility required to meet this challenge. The breadth of the portfolio enables developers to choose devices that best fit their application needs, freeing them to invest in differentiating aspects of their design.
"As we approach the milestone of 75 billion connected devices, we are entering a new era of edge computing, requiring us to fundamentally rethink how to best architect a flexible MCU portfolio that is scalable, optimised and can be the foundation for energy-efficient industrial and IoT edge applications today and in the decades to come," said Ron Martino, executive vice president and general manager of Edge Processing for NXP Semiconductors. "By building on our strong legacy in MCUs, this new portfolio will offer the performance and integration needed to address the real-time workloads for the next wave of innovation."
The four series in the portfolio are developed to simplify migration and scale up or down as required with maximal software reuse to minimise development costs. The portfolio is based on high-performance Arm Cortex-M cores. It incorporates a comprehensive set of peripherals for design flexibility. The devices feature up to 4MB of on-chip flash memory, low power cache and advanced memory management controllers, and up to 1MB of on-chip SRAM to enhance the real-time performance of edge applications.
Machine learning and run-time inference will be supported by the company's eIQ ML software development environment. Developers can employ the easy-to-use tools provided by eIQ to train ML models targeting the NPU or the CPU core and deploy them on the MCU. The families built following its security-by-design approach will provide secure boot with an immutable root-of-trust, hardware-accelerated cryptography and, on select families, a built-in EdgeLock secure subsystem.