1 GHz & Arm Cortex-M4 MCU For Superior Edge Application Performance

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NXP’s graphics accelerator, embedded security system, GHz Cortex-M7 core among others provide enhancement to Machine Language (ML) and IoT as well

NXP Semiconductors, has announced the availability of the i.MX RT1170 family of MCUs that enhance performance, reliability and high levels of integration to propel industrial, IoT and automotive applications. Through this availability, the company aims to reinforce its commitment towards building advanced edge computing technology with its EdgeVerse portfolio of solutions

“NXP saw the potential early on to create high-performance crossover MCUs, utilizing the latest applications processor architecture and design philosophies,” said Geoff Lees, senior vice president and general manager of Microcontrollers at NXP. “Now, with the i.MX RT1170 breaking the GHz barrier, we have opened up edge computing to all these technological possibilities.”

Enriched visual experience

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The i.MX RT1170 MCU includes a dual-core architecture with the Arm® Cortex®-M7 core that runs up to 1GHz and Cortex-M4 that runs up to 400MHz.

NXP’s 2D vector graphics core and pixel processing pipeline (PxP) 2D graphics accelerator with support for Open VG 1.1 API, enables the development of attractive user interfaces at low power by off-loading intensive graphics rendering to the GPU. The GHz core brings 720p displays at 60fps and 1080p HD screens at 30fps to create immersive visual experiences. The combination of a GPU and a high-performance core can be especially useful for smart home, industrial, and automotive cockpit applications.

Secure embedded system

For securing the embedded processor, the i.MX RT1170 family incorporates NXP’s EdgeLock 400A embedded security sub-system, that includes High Assurance Boot (HAB) – NXP’s version of secure boot, secure key storage, SRAM-based PUF (physically unclonable function), high performance crypto accelerators for AES-128/256, Elliptical Curve Cryptography, RSA-4096 encryption algorithms, hashing acceleration for SHA-256/512, in addition to tamper detection. The MCU also features in-line encryption engine (IEE) and on-the-fly decryption engines (OTFAD) to address the challenge of protecting the confidentiality of data stored in internal and external memories with no latency impact. The IEE is designed to encrypt and decrypt on-chip SRAM and external SRAM/PSRAM/DRAM, while OTFAD operates on external serial and parallel flash memories.

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Quick interrupt response

It also delivers an interrupt response time of 12ns, 6468 CoreMark score and 2974 DMIPS (Dhrystone Million Instructions per Second) while executing on-chip memory. The new MCU integrates up to 2MB of on-chip SRAM, including 512KB that can be configured as TCM with Error Code Correction (ECC) for Cortex-M7 use, and 256KB of TCM with ECC for Cortex-M4 use.

Enhanced ML performance

The GHz Cortex-M7 core enhances ML performance for voice, vision and gesture recognition, natural language understanding, data analytics, and digital signal processing (DSP) functions. The combination of GHz performance and high-density on-chip memory speeds up facial recognition inference time by up to 5x as compared to present fast MCUs in the market, thus improving processing bandwidth accuracy and providing immunity against spoofing. The GHz core is also efficient in executing computationally challenging voice recognition, including audio pre-processing (echo cancellation, noise suppression, beamforming, and barge-in) for improved cognition.

The i.MX RT1170 dual-core system pairs a high-performance core and a power-efficient core with independent operational power supplies which enables developers to run applications in parallel or reduce power consumption by turning off unused individual cores. For example, the energy-efficient Cortex-M4 core can be dedicated to time-critical control applications, such as sensor hub and motor control, while the main core runs more complex applications. Additionally, its dual-core system can run ML applications in parallel, such as face recognition with natural language processing to create human-like user interactivity.

“As we move towards a world of a trillion connected devices, businesses are looking for real-time data insights, driving an increased requirement for on-device intelligence,” said Dipti Vachani, senior vice president and general manager of the Automotive and IoT Line of Business at Arm. “The i.MX RT1170 family efficiently combines enhanced on-device processing with low-latency performance, significantly lowering the bill of materials (BOM) cost, while pushing the boundaries of what’s possible for embedded and IoT applications.”

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