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NXP’s MCU features 325 MHz Cortex-M33 with 172x AI acceleration

By Aimee Kalnoskas September 24, 2024

NXP Semiconductors has introduced the i.MX RT700 crossover MCU family, designed for AI-enabled edge devices. The i.MX RT700 integrates up to five cores, including a primary Arm Cortex-M33 running at 325 MHz, a Cadence Tensilica HiFi 4 DSP for advanced audio processing, and NXP’s eIQ Neutron Neural Processing Unit (NPU). The MCU offers up to 7.5MB of ultra-low power SRAM with zero wait-state access and delivers a 30-70% reduction in power consumption compared to previous generations.

The eIQ Neutron NPU significantly accelerates AI workloads, providing up to 172x faster image classification and up to 18x faster anomaly detection, while reducing energy per inference by up to 119x compared to running on the Cortex-M33 alone. Power-saving features include adaptive deep sleep techniques, optimized clock architectures with low-power cache schemes, and advanced wake/sleep cycle management.

For enhanced system performance, the i.MX RT700 integrates a high-efficiency DC-DC converter, a basic memory management unit, and supports improved analog peripherals. It is NXP’s first crossover MCU to support the eUSB standard, enabling USB 2.0 interfaces to operate at I/O voltages of 1 V or 1.2 V instead of 3.3 V. Security features include an EdgeLock Secure Enclave (Core Profile) providing secure boot with battery saving mode, secure update, seamless memory encryption, and secure data access. The MCU also incorporates a physically unclonable function (PuF) for device authentication.

The i.MX RT700 family is designed to comply with emerging cybersecurity regulations such as the U.S. Trust Mark and the European Cyber Resilient Act, as well as the ETSI 303 645 standard for consumer devices. The MCU is currently in the sampling phase for qualified early-access customers, with full technical specifications and availability information accessible at nxp.com/RT700.

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Filed Under: AI, Applications, Microcontrollers, Networking, Products
Tagged With: micontroller, neural networking, nxp
 

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