Geniatech launches OSM Size-L modules with Renesas RZ/G2L, Rockchip RK3566

Rockchip RK3566 OSM module

Geniatech has introduced LGA system-on-modules compliant with the SGET OSM (Open Standard Module) Size-L standard and designed to be soldered directly on the carrier board. Two models have been launched with the SOM-G2L-OSM equipped with Renesas RZ/G2L Arm Cortex-A55/M33 processor, and the SoM-3566-OSM powered by a Rockchip RK3566 quad-core Cortex-A55 SoC. SOM-G2L-OSM module Specifications: SoC – Renesas RZ/G2L dual-core Cortex-A55 processor, Cortex-M33 real-time core,  Arm Mali-G31 GPU, H.264 video encoder/decoder System Memory – 1GB RAM (2GB/4GB optional) Storage – 8GB eMMC flash (16GB/32GB optional) 662 contacts with Display – 1x MIPI DSI, 1x RGB Camera – 1x MIPI CSI Audio – I2S Networking – 2x Gigabit Ethernet USB – 1x USB OTG 2.0, 1x USB 2.0 host Serial – 2x CAN bus SDIO 3.0 Low-speed I/Os – 5x UART including debug, 2x I2C, 3x SPI, 3x PWM, 16x GPIO, 2x ADC Dimensions – 45 x 45 mm (OSM Size-L form […]

Turing Pi 2 mini-ITX cluster board supports RK3588 based Turing RK1, Raspberry Pi CM4, and NVIDIA Jetson SoMs (Crowdfunding)

Turing Pi 2

We first covered the Turing Pi V2 mini-ITX cluster board supporting up to four Raspberry Pi CM4 or NVIDIA Jetson SO-DIMM system-on-module in August 2021. The company has now launched the Turing Pi 2 on Kickstarter with a little surprise: the Turing RK1 module with Rockchip RK3588 Cortex-A76/A55 processor and up to 32GB RAM. The board allows you to mix and match modules (e.g. 3x RPi CM4 + 1x Jetson module as on the photo below), and with SATA ports, Gigabit Ethernet networking, USB 3.0 ports, mPCIe socket, you could build a fairly powerful homelab, learn Kubernetes, or self-host your own apps. Turing Pi 2 specifications: SoM interface – 4x 260-pin SO-DIMM slots for up to four Raspberry Pi CM4 with Broadcom quad-core Cortex-A72 processor, up to 8GB RAM, up to 32GB eMMC flash (adapter needed) NVIDIA Jetson Nano/TX2 NX/Xavier NX SO-DIMM system-on-modules with up to 6x Armv8 cores, and […]

Trying out Edge Impulse machine learning platform on XIAO BLE Sense board

double-sided sticky tape boards

I had seen the Edge Impulse development platform for machine learning on edge devices being used by several boards, but I hadn’t had an opportunity to try it out so far. So when Seeed Studio asked me whether I’d be interested to test the nRF52840-powered XIAO BLE Sense board, I thought it might be a good idea to review it with Edge Impulse as I had seen a motion/gesture recognition demo on the board. It was quite a challenge as it took me four months to complete the review from the time Seeed Studio first contacted me, mostly due to poor communications from DHL causing the first boards to go to customs’ heaven, then wasting time with some of the worse instructions I had seen in a long time (now fixed), and other reviews getting in the way. But I finally managed to get it working (sort of), so let’s […]

ZUBoard 1CG – A low-cost AMD Xilinx Zynq UltraScale+ ZU1CG MPSoC FPGA development board

ZUBoard 1CG development board

Avnet ZUBoard 1CG is a development board featuring the new entry-level AMD Xilinx Zynq UltraScale+ ZU1CG dual-core Cortex-A53 MPSoC with 81K FPGA system logic cells, equipped with 1GB LPDDR4 RAM, as well as SYZYGY connectors and mikroBus expansion for Click boards. Priced at $159, the board may offer a good opportunity to get started with Zynq UltraScale+ MPSoC, as it’s quite cheaper than boards based on ZU3 devices such as Ultra96-V2 or MYD-CZU3EG. Avnet says the board is suitable for artificial intelligence, machine learning, embedded vision, embedded processing, and robotics applications. ZUBoard 1CG specifications: SoC – AMD/Xilinx ZU+ MPSoC ZU1CG with Dual Cortex-A53 APU @ up to 1.3 GHz and dual Cortex-R5 RPU @ up to 533 MHz 256KB On-chip Memory 81,900 FPGA Logic Cells System Memory – 1GB LPDDR4 with on-chip ECC Storage – 256Mbit QSPI flash, microSD card, both bootable Networking –  10/100/1000M Gigabit Ethernet RJ45 port USB […]

MediaTek unveils Genio 1200 premium AIoT processor with 4.8 TOPS NPU

MediaTek Genio 1200

MediaTek has introduced the Genio platform for AIoT devices, and unveiled the first chip of the Genio family with the Genio 1200 Octa-core Cortex-A78/A55 processor with a 4.8 TOPS NPU, 4K video support, and designed for premium AIoT products. The chip is manufactured with a 6nm processor, is said to consume less than 8W, supports dual 4Kp60 video output and up to 48MP @ 30 fps video capture, and  WiFi 6, Bluetooth 5.2 and 5G connectivity can be added through add-in chips. Targets applications include Smart Home appliances, HMI, industrial IoT, robotics, and more. MediaTek Genio 1200 key features and specifications: CPU – Octa-core processor with four Cortex-A78 cores @ up to 2.2 GHz, four Cortex-A55 cores GPU – Arm Mali-G57 MC5 GPU VPU Encoding up to 4Kp60 with H.265/HEVC Decoding up to 4Kp90, AV1, VP9, HEVC, H.264 codecs supported AI accelerator – Dual-core Mediatek AI processor (APU) with INT8, INT16, […]

Canaan K510 CRB RISC-V AI development kit ships with dual-camera module and LCD display

Canaan K510 dual-core RISC-V AI development board

Last summer, Canaan introduced the Kendryte K510 tri-core RISC-V AI processor, now also known as Canaan K510, as an updated version of the Kendryte K210 with a much higher 3 TOPS of performance, but at the time, there were no development board and SDK. But I’ve now just been informed of the availability of the Canaan Kendryte K510 CRB (customer reference platform) AI development kit with camera module and LCD display, as well as a software development kit with U-Boot, Linux, and AI tools which can be used to develop smart audio and computer vision applications. Kendryte K510 CRB-Kit development kit specifications: SoC – Canaan Kendryte K510 dual-core RISC-V64 CPU up to 800MHz and 1x RISC-V DSP up to 800MHz for up to 3 TOPS AI performance, ultra-low-power wake-up VAD, H.264 video encoding up to 2 channels @ 1080p60 System Memory – 512 MB LPDDR3 @ 1600 MHz Storage – […]

Allwinner V853 Arm Cortex-A7 + RISC-V SoC comes with 1 TOPS NPU for AI Vision applications

Allwinner V853

Allwinner V853 SoC combines an Arm Cortex-A7 core with a Xuantie E907 RISC-V core, and a 1 TOPS NPU for cost-sensitive AI Vision applications such as smart door locks, smart access control, AI webcams, tachographs, and smart desk lamps. Manufactured with a 22nm process, the SoC comes with an ISP image processor and Allwinner Smart video engine capable of up to 5M @ 30fps H.265/H.264 encoding and 5M @ 25fps H.264 decoding, offers parallel CSI and MIPI CSI camera interfaces, and well as MIPI DSI and RGB display interfaces. Allwinner V853 specifications: CPU Arm Cortex-A7 CPU core @ 1 GHz with 32 KB I-cache, 32 KB D-cache, and 128 KB L2 cache Alibaba Xuantie E907 RISC-V core with 16 KB I-cache and 16 KB D-cache NPU (Neural network Processing Unit) – Up to 1 TOPS for V853 and 0.8 TOPS for V853S,  embedded 128KB internal buffer, support for TensorFlow, Caffe, […]

Axiomtek AIE900-XNX – A 5G connected fanless Edge AI system for AMR, AGV, and computer vision

Axiomtek AIE900-XNX

Axiomtek AIE900-XNX is a fanless Edge AI computing system powered by NVIDIA Jetson Xavier NX system-on-module designed for autonomous mobile robots (AMR), automated guided vehicles (AGV), and other computer vision applications. The system delivers up to 21 TOPS thanks to the 6-core NVIDIA Carmel ARM v8.2 (64-bit) processor, NVDLA accelerators, and 384-core NVIDIA Volta architecture GPU found in the Jetson Xavier NX module. The AIE900-XNX Edge AI computer also comes with a 5G module for high-speed cellular connectivity and supports SerDes, PoE, and MIPI CSI cameras for video processing. Axiomtek AIE900-XNX specifications: NVIDIA Jetson Xavier NX system-on-module with CPU – 6-core NVIDIA Carmel Armv8.2 64-bit CPU with 6 MB L2 + 4 MB L3 cache GPU – 384-core NVIDIA Volta GPU with 48 Tensor Cores AI Accelerator – 2x NVDLA System Memory – 8GB 128-bit LPDDR4x onboard Storage – 16GB eMMC flash Storage –  M.2 Key M 2280 with PCIe […]