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Posted on by Jean-Luc Aufranc (CNXSoft) - 3 Comments on LattePanda Mu review – Part 1: an Intel N100 Compute Module tested with Windows 11, carrier boards with PCIe slots

LattePanda Mu review – Part 1: an Intel N100 Compute Module tested with Windows 11, carrier boards with PCIe slots

LattePanda Mu Full Carrier Windows 11 Review

Last April, DFRobot launched the LattePanda Mu x86 Compute Module powered by an Intel N100 Alder-Lake processor with 8GB RAM and a 64GB eMMC flash along with Lite and Full function carrier boards for evaluation. End customers will typically design their own carrier board without having to take of high-speed signals for the LPDDR5 memory and other complexities during the PCB layout. DFRobot has sent us the LattePanda Mu module for review along with the Lite and Full Function carrier boards, a heatsink for passive cooling, and an active cooler so we can compare both cooling solutions.  Let’s have a look at the LattePanda Mu module and accessories before testing the kit with the Windows 11 operating system, including the PCIe x4 slot. LattePanda Mu kit unboxing The parcel included three retail boxes. The smallest box housed the LattePanda Mu Compute Module, a heatsink, and an active cooler. The second […]

Posted on by Debashis Das - 7 Comments on NiCE5340 SoM packs Nordic nRF5340 MCU, Lattice iCE40 FPGA, and 11 sensors into a tiny 29x16mm form factor

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 […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 1 Comment on MYiR Tech launches AMD XC7A100T Artix-7 FPGA system-on-module and development board with PCIe, SFP+ cages, dual GbE

MYiR Tech launches AMD XC7A100T Artix-7 FPGA system-on-module and development board with PCIe, SFP+ cages, dual GbE

AMD XC7A100T FPGA development board

MYIR MYC-J7A100T is a System-On-Module (SoM) powered by an AMD/Xilinx Artix-7 XC7A100T FPGA with up to 101,440 logic cells, 512MB DDR3 memory, 32MB QSPI FLASH, 32KB EEPROM, DC-DC power management, and other integral circuits in a compact 69.6 x 40mm form factor. The module exposes up to 178 FPGA I/Os, four pairs of GTP high-speed transceiver interfaces, and a JTAG interface through its 260-pin edge connector. MYiR also provides a development board for the MYC-J7A100T module which looks like a PCIe 2.0 card and comes with SFP+ cages, HDMI input and output ports, dual GbE, and a GPIO expansion header. MYIR MYC-J7A100T system-on-module Specifications: FPGA – AMD/Xilinx XC7A100T Artix-7 FPGA (XC7A100T-2FGG484I) with 101,440 logic cells 4,860 Kb of Block RAM 240 DSP slices 8 GTP transceivers capable of reaching speeds up to 6.6Gb/s PCIe Gen2 x4  interface Up to 300x single-ended I/Os System Memory – 512MB DDR3 Storage – 32MB […]

Posted on by Sponsored Post - No Comments on High-Performance Edge Computing with PICMG COM-HPC: A Virtual Event Series (Sponsored)

High-Performance Edge Computing with PICMG COM-HPC: A Virtual Event Series (Sponsored)

COM-HPC Mini Academy

Doug Sandy is the CTO of PICMG, an industry consortium focused on developing open and modular computing specifications. He, along with dozens of member companies who participated in the development of the upcoming COM-HPC specification, believes that engineers building edge systems need new hardware. “Between converged network rollouts and advances in AI, the hardware requirements for edge computing have changed,” Sandy says. “Modern edge workloads need a combination of high-end compute, managed power consumption, and low-latency data transmission.” These merging requirements led PICMG to pursue a new standard for high-performance computing. The result is COM-HPC, a computer-on-module specification that brings unprecedented computing power and I/O bandwidth to resource-constrained applications. First ratified in 2021, COM-HPC has expanded to address various use cases. Most recently, COM-HPC Mini was created to address small form factor applications. “COM-HPC Mini introduces a credit-card-sized form factor with features like expanded connectivity support, efficient thermal management, and […]

Posted on by Jean-Luc Aufranc (CNXSoft) - No Comments on Ochin V2 tiny Raspberry Pi CM4 robotics carrier board gets micro HDMI port, Fast Ethernet support

Ochin V2 tiny Raspberry Pi CM4 robotics carrier board gets micro HDMI port, Fast Ethernet support

Ochin V2 CM4 robotics carrier board and USB-C board

Ochin V2 is an update to the tiny Ochin Raspberry Pi CM4 carrier board for robotics applications and drones that adds a micro HDMI port, support for Fast Ethernet through pads or a GHS connector (no RJ45 connector), two user LEDs, and a few other changes. The form factor remains the same at just 55 x 40 x 4.7mm, or about the size of a Raspberry Pi Compute Module 4, which in combination with a range of USB, UART, I2C, and SPI interfaces, makes it an ideal candidate for space-constrained applications such as robotics system or UAVs. Ochin V2 specifications (differences against Ochin v1 shown in bold or strikethrough): Supported modules – Raspberry Pi CM4 with Broadcom BCM2711 quad-core Cortex-A72 processor, up to 8GB RAM, up to 32GB eMMC flash (the CM4 Lite is not supported since there’s no microSD card on the board), 4Kp60 H.265 decode, 1080p30 H.264 encode, […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 1 Comment on Olimex open-source hardware NXP i.MX 8M Plus industrial-grade SoM runs mainline Linux

Olimex open-source hardware NXP i.MX 8M Plus industrial-grade SoM runs mainline Linux

Olimex i.MX 8M Plus SOM mainline Linux

Olimex has just announced the iMX8MP-SOM-4GB-IND industrial-grade, open-source hardware system-on-module based on NXP i.MX 8M Plus Arm AI SoC and 4GB LPDDR4 thar runs mainline Linux and operates in the -20°C to +85°C temperature range. The CPU module also features a wide range of interfaces exposed through female headers including HDMI 2.0, MIPI-DSI, LVDS, dual MIPI CSI, dual Gigabit Ethernet, CAN FS and more. Olimex also designed the iMX8MP-SOM-EVB evaluation board for easy evaluation. Olimex iMX8MP-SOM-4GB-IND system-on-module Specifications: SoC – NXP i.MX 8M Plus (MIMX8ML8CVNKZAB) CPU Quad-core Arm Cortex-A53 processor @ up to 1.6 GHz Arm Cortex-M7 real-time core @ 800 MHz Cache – 512KB GPU – Vivante GC7000UL 3D GPU, Vivante GC520L 2D GPU VPU – 1080p H.265/H.264 video decoder & encoder DSP HiFi 4 DSP AI accelerator – 2.3 TOPS Neural Processing Unit (NPU) System Memory – 4GB LPDDR4 Storage – EEPROM for Linux configuration Display and camera […]

Posted on by Debashis Das - 1 Comment on Avnet AI Vision Development Kit features Qualcomm QCS6490 SoC, dual camera, GbE, and USB-C PD

Avnet AI Vision Development Kit features Qualcomm QCS6490 SoC, dual camera, GbE, and USB-C PD

QCS6490 Vision AI Development Kit

Just last month at Embedded World 2024, Qualcomm announced its RB3 Gen 2 Platform based on the QCS6490 processor with Cortex-A78 and A55 processing cores and 12 TOPS of AI power. Building on this, Avnet has recently launched the Avnet AI Vision Development Kit, also based on the QCS6490 SoC. The kit includes a dual camera setup, Gigabit Ethernet connectivity, USB-C Power Delivery, and a host of other features for applications like inventory and asset monitoring, drone/UAV/other mobile vision-AI edge compute applications, and multi-camera security systems with recognition. Previously we have written about similar AI dev kits including Allwinner V853 100ASK-V853-Pro, Sipeed Maix-III devkit, RZBoard V2L, and many other AI vision development boards feel free to check those out if you are interested in the topic. Avnet AI Vision Development Kit specifications SM2S-QCS6490 SMARC Compute Module: CPU – 4x Arm Cortex-A78 (up to 2.7 GHz), 4x Arm Cortex-A55 (up to […]

Posted on by Debashis Das - 3 Comments on NetBurner SOMRT1061 – A stamp-sized dual Ethernet SoM powered by NXP’s i.MX RT1061 crossover processor

NetBurner SOMRT1061 – A stamp-sized dual Ethernet SoM powered by NXP’s i.MX RT1061 crossover processor

i.MX RT1061 Embedded System on Module SOMRT1061

The NetBurner SOMRT1061 is a System-on-Module (SoM) that comes in a very compact stamp-sized footprint that measures just 25.4mm x 25.4mm, yet boasts a rugged design and 67 usable GPIO pins with edge connectors. These features make this SoM ideal for a wide range of medical, industrial, and robotics applications. The SoM is built around the NXP’s i.MX RT1061 Arm Cortex M7 SoC, and features 1MB of internal SRAM, 32MB of external RAM, and 8MB of flash storage. It also features dual 10/100M Ethernet with PTP, an on-die temperature sensor, three FlexIO modules, two USB OTG 2.0 controllers, I2C, SPI, ADC, SD Card, CAN, UART, and many more. NetBurner SOMRT1061 System-on-Module (SOM) Specifications SoC  –  NXP i.MX RT1061 Arm Cortex-M7 @ 528MHz. Memory 1MB SRAM on the processor 32MB of external RAM Storage Flash – 1MB boot, 8MB application SDHC – Flash card interface Ethernet Up to two 10/100 Ethernet […]

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