Alif Semi Ensemble E1C is an entry-level Cortex-M55 MCU with a 46 GOPS Ethos-U55 AI/ML accelerator

Alif Ensemble E1C AI/ML Cortex-M55 microcontroller

Alif Semi Ensemble E1C is an entry-level addition to the company’s Ensemble Cortex-A32M35 processors and microcontrollers with Ethos-U55 microNPUs that targets the very edge with a 160 MHz Cortex-M55 microcontroller and a 46 GOPS Ethos-U55 NPU. The Ensemble E1C is virtually the same as the E1 microcontroller but with less memory (2MB SRAM) and storage (up to 1.9MB non-volatile MRAM), and offered in more compact packages with 64, 90, or 120 pins as small as 3.9 x 3.9mm. Alif Semi Ensemble E1C specifications: CPU – Arm Cortex-M55 core up to 160 MHz with Helium Vector Processing Extension, 16KB Instruction and Data caches, Armv8.1-M ISA with Arm TrustZone; 4.37 CoreMark/MHz GPU – Optional D/AVE 2D Graphics Processing Unit MicroNPU – 1x Arm Ethos-U55 Neural Processing Unit with 128 MAC; up to 46 GOPS On-chip application memory Up to 1.9 MB MRAM Non-Volatile Memory Up to 2MB Zero Wait-State SRAM with optional […]

NiCE5340 SoM packs Nordic nRF5340 MCU, Lattice iCE40 FPGA, and 11 sensors into a tiny 29x16mm form factor

Stefano Viola's NiCE5340 SoM

Stefano Viola’s NiCE5340 SoM is built around a Nordic Semi nRF5340 Bluetooth SoC, an iCE40 FPGA, 11 sensors, a battery charger, and various other peripherals in a 29×16 mm form factor. The nRF5340 used in the SoM is a low-power, dual-core Arm Cortex-M33 SoC with Bluetooth 5.4, Bluetooth LE (BLE), Thread, Zigbee, and other proprietary protocols. Meanwhile, the Lattice iCE40 FPGA features 3520 logic cells, 80 Kbits of embedded Block RAM, I2C, and SPI blocks, and many other features that make it suitable for applications like environmental monitoring, health tracking, and others. Previously, we have written about Unexpected Maker NANOS3, TinyS3, FeatherS3, and ProS3 boards, and ESP32-S3 4G dev board which all fall under the tiny and compact board category but this is the first time we have seen an MCU board with so many features built into a module of that size. Stefano Viola’s NiCE5340 SoM Specification ICs Nordic […]

DFM8001 indoor energy harvesting kit harnesses solar energy (and mechanical, thermal, RF energy with extra hardware)

DFM8001 Indoor Ambient Energy Harvesting Kit

DFRobot DFM8001 indoor ambient energy harvesting kit can power IoT devices by harnessing solar energy, and the company claims it can also capture mechanical, thermal, and RF energy from the local environment but there’s no way to do that with that kit without additional hardware. The DFRobot kit is comprised of an evaluation board with the company DFM8001 energy harvesting module, two pluggable supercapacitors, and a solar panel used as power input. You could also use other sources emitting at least 150 mV gathering energy from RF, thermal, or mechanical sources. The board features two outputs one low-voltage (1.2-1.8V) terminal up to 20mA, and a high-voltage (1.8V-4.1V) terminal up to 80mA, and two battery connectors plus a few jumpers for configuration. DFM8001 energy harvesting kit specifications: Operating voltage – 3.3V to 5.5V DC Cold start condition – Input > 400mV 15uW Sustaining voltage after cold start – 150mV. Input voltage […]

Conexio Stratus Pro – A battery-powered nRF9161 development kit with LTE IoT, DECT NR+, GNSS connectivity (Crowdfunding)

Conexio Stratus Pro nRF9161 IoT prototyping kit

Conexio Stratus Pro is a tiny IoT development kit based on Nordic Semi nRF9161 system-in-package (SiP) with LTE-M/NB-IoT, DECT NR+, and GNSS connectivity and designed to create battery-powered cellular-connected electronic projects and products such as asset trackers, environmental monitors, smart meters, and industrial automation devices. Just like the previous generation Conexio Startus board based on the Nordic Semi nRF9160 cellular IoT SiP, the new Conexio Stratus Pro board supports solar energy harvesting and comes with a Feather form factor and Qwiic connector for each expansion. Conexio Stratus Pro specifications: System-in-package – Nordic Semi nRF9161 SiP MCU – Arm Cortex-M33 clocked at 64 MHz with 1 MB Flash pre-programmed MCUBoot bootloader, 256 KB RAM Modem Transceiver and baseband 3GPP LTE release 14 LTE-M/NB-IoT support DECT NR+ ready GPS/GNSS receiver RF Transceiver for global coverage supporting bands: B1, B2, B3, B4, B5, B8, B12, B13, B17, B18, B19, B20, B25, B26, B28, […]

EdgeCortix SAKURA-II Edge AI accelerator deliver up to 60 TOPS in an 8W power envelope

SAKURA-II M.2 and PCIe Edge AI accelerators

EdgeCortix has just announced its SAKURA-II Edge AI accelerator with its second-generation Dynamic Neural Accelerator (DNA) architecture delivering up to 60 TOPS (INT8) in an 8Watts power envelope and suitable to run complex generative AI tasks such as Large Language Models (LLMs), Large Vision Models (LVMs), and multi-modal transformer-based applications at the edge. Besides the AI accelerator itself, the company designed a range of M.2 modules and PCIe cards with one or two SAKURA-II chips delivering up to 120 TOPS with INT8, 60 TFLOPS with BF16 to enable generative AI in legacy hardware with a spare M.2 2280 socket or PCIe x8/x16 slot. SAKURA-II Edge AI accelerator SAKURA-II key specifications: Neural Processing Engine – DNA-II second-generation Dynamic Neural Accelerator (DNA) architecture Performance 60 TOPS (INT8) 30 TFLOPS (BF16) DRAM – Dual 64-bit LPDDR4x (8GB,16GB, or 32GB on board) DRAM Bandwidth – 68 GB/sec On-chip SRAM – 20MB Compute Efficiency – […]

MemryX MX3 edge AI accelerator delivers up to 5 TOPS, is offered in die, package, and M.2 and mPCIe modules

MemryX MX3 EVB

Jean-Luc noted the MemryX MX3 edge AI accelerator module while covering the DeGirum ORCA M.2 and USB Edge AI accelerators last month, so today, we’ll have a look at this AI chip and corresponding modules that run computer vision neural networks using common frameworks such as TensorFlow, TensorFlow Lite, ONNX, PyTorch, and Keras. MemryX MX3 Specifications MemryX hasn’t disclosed much performance stats about this chip. All we know is it offers more than 5 TFLOPs. The listed specifications include: Bfloat16 activations Batch = 1 Weights: 4, 8, and 16-bit ~10M parameters stored on-die Host interfaces – PCIe Gen 3 I/O and/or USB 2.0/3.x Power consumption – ~1.0W 1-click compilation for the MX-SDK when mapping neural networks that have multiple layers Under the hood, the MX3 features MemryX Compute Engines (MCE) which are tightly coupled with at-memory computing. This design creates a native, proprietary dataflow architecture that utilizes up to 70% […]

NanoCell V2.1 battery-powered ESP32-C3 IoT board runs ESPHome for Home Assistant integration

nanocell v2 stack

The NanoCell V2.1 is a development board built around the Espressif ESP32-C3 SoC (system-on-a-chip) preloaded with ESPHome firmware for low-power applications and improved Lithium battery management. The development board is a white printed circuit board with gold-plated contacts and a battery fuel-gauge IC, designed by Frapais’ lab in Greece. As the name suggests, the NanoCell V2.1 is the latest in a series of iterations of ESP32-C3-based devices targeted at low-power applications. Compared to earlier versions, it offers a better user experience and improved power efficiency. It features a buck-boost converter that reduces standby current consumption to 66uA (excluding the current consumed by the ESP32 module). The battery management system (BMS) integrated circuit supports accurate capacity measurement and protects connected Lithium batteries from overcharging and other harmful scenarios. Also, two LEDs on the board serve as power and charging indicators to relay the board’s status. It is based on the same […]

M5Stack CoreMP135 – A Linux-powered industrial controller based on STM32MP135 Cortex-A7 MPU

M5Stack CoreMP135 industrial control host

M5Stack CoreMP135 is an industrial control host powered by the STM32MP135DAE7 Arm Cortex-A7 core microprocessor running at 1GHz, equipped with up to 512MB DDR3L SDRAM memory, and loaded with high-performance interfaces such as two Gigabit Ethernet ports, three USB ports, two CAN FD interfaces, two Grove interfaces, and an “HD” video output. An integrated PWR485 communication board bundles a 9V to 24V power input and an RS485 interface. The device also features a microSD card slot for storage, a small IPS capacitive touch screen, and a 1W speaker for human-machine interaction. The CoreMP135 is designed for low-power consumption and uses an Allwinner AXP2101 chip for power management. It supports scheduled wake-up and sleep with an integrated real-time clock (BM8563 module). The device runs Linux and comes with a microSD card loaded with the Debian operating system, simplifying setup and allowing usage out of the box. A DIN rail base plate […]

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