With enhanced power efficiency and integrated AI capabilities, this new solution aims to enhance wearables, consumer medical gadgets, smart home technology, and human-machine interface (HMI) devices.
NXP Semiconductors has introduced the i.MX RT700 family, an advanced multicore processor designed to meet the demands of AI-enabled edge applications. With ultra-low power consumption and integrated AI capabilities, this new product aims to enhance devices like wearables, consumer medical gadgets, smart home systems, and human-machine interface (HMI) solutions. It offers an ideal balance of performance, efficiency, and functionality, building on the success of the earlier i.MX RT500 and RT600 crossover MCUs. This launch reflects the company’s commitment to empowering next-generation devices by offering extended battery life, advanced processing, and AI acceleration.
The key features include:
- 7.5 MB SRAM with 30 partitions to optimize multicore access
- Supports JPEG/PNG decoding and vector graphics with a MIPI-DSI interface
- Reduces power consumption by 70% compared to previous models
- eUSB support with compatibility for USB 2.0 devices
- Flashless design with three xSPI controllers for external flash or RAM connections
The family features integrated eIQ Neutron Neural Processing Unit (NPU) for AI/ML tasks, along with a multicore design that includes dual Arm Cortex-M33 processors. One core serves as the primary processor running at 325 MHz, while the other runs at 250 MHz for low-power “always-on” applications. This architecture includes a Cadence Tensilica® HiFi 4 DSP for high-performance signal processing, complemented by a HiFi 1 DSP for continuous low-power operations.
Optimized for AI and Embedded Systems
Designed to power the AI-enabled edge including wearables, consumer medical, smart home, and HMI devices, the family delivers an optimized combination of high performance, extensive integration, advanced functionality, and power efficiency. Featuring a RISC-V EZH-V coprocessor and a scalable NPU, it offers a 172x performance boost for AI models while minimizing energy consumption. With flexible memory configurations and advanced DSPs, it ensures seamless operation across various embedded applicatioIt’s compact packaging supports space-constrained designs, making it ideal for wearables, fitness trackers, and augmented reality devices.
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