Alif Semiconductor Expands their Groundbreaking Ensemble family with E1C, a MCU that Packs 46 GOPs of Extreme Low-power On-chip AI/ML Processing Into Tiny Footprint

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Jun 18, 2024, 09:00 ET

The new E1C microcontroller with on-chip NPU and large tightly coupled memory opens up new potential for machine learning in deeply space- and power-constrained embedded applications and IoT endpoints.
Sophisticated aiPM^™power management system and ultra-efficient AI operation make the E1C ideal for wearable and other systems powered by small batteries.

PLEASANTON, Calif., June 18, 2024 /PRNewswire/ -- Alif Semiconductor^®, a leading global supplier of secure, connected, power efficient Artificial Intelligence and Machine Learning (AI/ML) microcontrollers (MCUs) and fusion processors, today launched the Ensemble^® E1C, an MCU series which combines rich digital and analog capabilities with a low-power on-chip neural processing unit (NPU) in a new compact form factor.

Alif Semiconductor Expands their Groundbreaking Ensemble family with E1C, a MCU that Packs 46 GOPs of Extreme Low-power On-chip AI/ML Processing Into Tiny Footprint

This new Ensemble family MCU, which combines a 160MHz Arm^® Cortex^®-M55 CPU core with Helium^™ vector processing extension, an Arm Ethos^™-U55 NPU generating up to 46 GOPs, and up to 2MB of tightly coupled SRAM, is available in a tiny WLCSP package occupying a footprint of 3.9mm x 3.9mm.

The introduction of the E1C extends the highly scalable Ensemble family, providing a new entry-level option for OEMs that want to take advantage of Ensemble's unique combination of high AI performance and ultra-low power consumption implemented in a familiar Arm environment. The new E1C also shares the same architecture as the Balletto™ family, allowing for software re-use across the entire family, and easy migration of applications from one device to another.

Thanks to the efficient ML inferencing performance of the Ethos NPU and an advanced aiPM^™ power management system, the E1C can perform both AI/ML and application control functions at ultra-low power levels. This means manufacturers can bring advanced ML capabilities to products such as wearable devices that have extreme constraints on power and space. The E1C's capabilities are optimized for local ML workloads such as object recognition, speech recognition, sensor fusion, and adaptive audio noise cancellation, easing heavy dependence on the cloud to provide a better user experience.

"Alif already blazed a new trail in the industry for powerful and extremely efficient localized ML with the Ensemble family, and the new E1C series products squeeze those same capabilities into a smaller space with even more power-efficiency," said Reza Kazerounian, President and Co-Founder of Alif Semiconductor. "This progression opens more opportunities in applications for health monitoring, distributed sensing, audio processing and more for developers to reduce size, power, and cost."

Comprehensive feature set for connected IoT endpoints

The high AI performance of the E1C is matched by its power efficiency. The E1C's aiPM technology can dynamically power only the logic and associated memory that are in use at any given time, thus achieving the lowest overall system power consumption. The aiPM power management unit implements four system-level power modes including a Stop mode which draws just 700nA.

The Ethos-U55 NPU performs 128 MACs/cycle to give ML output of 46 GOPS, and enables on-the-fly weight decompression. This results in inferencing performance some 100x faster and more power-efficient than competing MCUs based on an Arm Cortex-M4 CPU provide. The E1C's digital cores are backed by up to 2MB of MRAM non-volatile memory alongside up to 2MB of zero wait-state SRAM. A high-speed OctalSPI interface enables expansion to external memory if required. Versions of E1C devices are offered with and without the NPU.

Providing a high level of system integration, the E1C features a rich set of analog and connectivity peripherals. Two 12-bit SAR ADCs and a 24-bit sigma-delta ADC, a 12-bit DAC and an internal reference voltage provide for fast, precise processing of signals from external sensors. Outputs can be displayed on rich color displays using a MIPI DSI^® display interface.

A broad selection of serial communications interfaces includes USB 2.0, SDIO, 2x CAN FD and I³C. Designers of connected devices can also benefit from the same low-power and high-performance characteristics of the E1C with the addition of built-in Bluetooth^® Low Energy connectivity by choosing the Balletto B1, launched by Alif on 9 April 2024.

Comprehensive security is a core attribute of the Ensemble family, and the E1C shares the same architecture. Its advanced secure enclave, which provides a solid hardware root-of-trust enabling secure key generation and storage, secure boot, cryptographic accelerators, and certificate management, eliminates the need for an external Secure MCU in endpoint AI devices.

The E1C is available in three package options:

For maximum space savings – 90-bump WLCSP
For maximum I/O while requiring only 4 PCB layers for routing – 120-bump FBGA
For maximum durability in harsh environments – 64-lead TQFP

Rich resources for evaluation and development

All Ensemble MCUs, including the E1C, are fully compatible with the Arm ecosystem of tools, development environments and software resources for efficient system development. For evaluation of the E1C, Alif supplies the DK-E1 development kit.

E1C devices and DK-E1 kits will be available to lead customers in August 2024 with production ramping in 4Q24.

For more information on E1C, please visit: https://alifsemi.com/ensemble-e1c-series/

About Alif Semiconductor:
Alif Semiconductor is the industry-leading supplier of next-generation secure AI/ML-enabled 32-bit microcontrollers. Since 2019, Alif's expanding offering of microcontrollers and fusion processors has been revolutionizing the way developers can create broad, scalable, and connected AI-enabled embedded applications that are genuinely power efficient. Alif Semiconductor is the only choice for power efficient microcontrollers that can handle heavy AI and ML workloads for battery-operated endpoint devices. For more information go to https://alifsemi.com/.

Related Links:
https://www.alifsemi.com/

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SOURCE Alif Semiconductor