Tuesday, June 25, 2024

AI-Enhanced 32-Bit MCUs And Fusion Processors

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The 32-bit microcontrollers and fusion processors enhance AI performance with efficient energy consumption tailored for Edge ML applications.

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Alif Semiconductor has announced the availability of its Ensemble product line, including 32-bit microcontrollers and fusion processors, through global distribution channels. The Ensemble series is designed to improve performance compared to traditional 32-bit MCUs in AI models. Alif’s architecture achieves this by integrating a microNPU with each CPU core. It can also improve AI/ML performance over traditional MCU cores, leading to a considerable overall increase in performance. This increase in performance does not lead to higher energy consumption, as each object detection inference consumes only 0.27 mJ, much less than typical MCUs.

The devices include a range of single-core and dual-core RTOS MCUs with Arm Cortex-M55 CPUs and optional Arm Ethos-U55 microNPUs for machine learning. The series also features triple- and quad-core fusion processors with Cortex-A32 CPUs that are compatible with operating systems such as Linux. The consistent architecture across the series supports software reuse for various project scales. Additionally, the protection measures prevent intellectual property theft, ensure code integrity, and safeguard against malware. Cryptography secures data within the device and during communication. The devices include integrated memory, peripherals, and power management. Alif’s aiPM technology optimizes battery life by selectively powering components as needed for efficient operation.

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“Early on, we saw a huge gap in the market.” said Mark Rootz, VP of Marketing at Alif Semiconductor. “There are many Edge ML applications that require 50 to 250 GOPs to become useful. Typical 32-bit MCUs can’t come close to that performance level, so to find a solution developers had to jump all the way to GPU-based accelerators at about the 1000 GOPs level which is extreme overkill in terms of power, size, cost, and complexity. Only Alif fills this gap in the middle. This is the sweet spot for battery-powered products on the Edge.” 

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Nidhi Agarwal
Nidhi Agarwal
Nidhi Agarwal is a journalist at EFY. She is an Electronics and Communication Engineer with over five years of academic experience. Her expertise lies in working with development boards and IoT cloud. She enjoys writing as it enables her to share her knowledge and insights related to electronics, with like-minded techies.

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