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DonglePi is a USB Dongle with a Raspberry Pi Header for your PC

While the newer Raspberry Pi A+, B+ and B2 boards feature the new 40-pin connector, the Raspberry Pi boards Model A and B have a 26-pin expansion header, but both are use to access GPIOs, UART, SPI, I2C and interface with external hardware, and many add-ons boards have been developed for the Raspberry Pi. But what if you’d like to use R-Pi add-ons board on your PC, or instead you are developing your own add-on board, but would like to do so directly on your PC for convenience? DonglePi is the answer. It’s a small USB dongle with Atmel SAMD21 MCU and a 26-pin Raspberry Pi compatible header, that you could use connect to your Android/Linux/Windows PC to play with GPIO, I2C, SPI, Serial, PWM just like on a Raspberry Pi, and using RPi/GPIO or smbus Python libraries for programming. The project is still in development, and so far most […]

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Xilinx Introduces Zynq UltraScale+ MPSoC with Cortex A53 & R5 Cores, Ultrascale FPGA

Xilinx Zynq-7000 dual core Cortex A9 + FPGA SoC family was announced in 2012, and provides a wide range of SoC with features and price range, and led to low cost ARM + FPGA such as ZedBoard, and more recently Parallela and MYiR Z-Turn boards. The company unveiled its successor with Zynq UltraScale+ MPSoC providing five times more performance per watt, with four ARM Cortex A53 cores, two ARM Cortex R5 real-time MCU cores, a Mali-400MP GPU, an UltraScale FPGA fabric manufactured with 16nm FinFET+ process. There are two main sub-families in Zynq Ultrascale+ MPSoC for “smarter control & vision”, and “smarter network”. Both share the same processing systems (CPU, GPU, MCU, Peripherals, Security), but the networking family has beefier FPGAs,  and lacks the H.264/H.265 video processing unit found in the control & vision version: Processing Systems Processor – Quad ARM Cortex A53 MPCore up to 1.3GHz Real-time Processor – […]

ArmSoM RK3588 AIModule7 NVIDIA Jetson Nano-compatible SOM
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Linaro 15.02 Release with Linux 3.19 and Android 5.0

Linaro 15.02 has just been released with Linux 3.19 (baseline), Linux 3.10.68 and 3.14.34 (LSK), Android 5.0.2, and Ubuntu Linaro Utopic. Listed changes for Linux Linaro are exactly the same as last month, except they’ve used Linux 3.9 release. Power management tools have been added to their AOSP build, and some work has been done for Android 5.0 on the new Hikey board. Here are the highlights of this release: Linux Linaro 3.19-2015.02 GATOR topic: version 5.20.1 updated integration-linaro-vexpress64 topic by ARM LT (FVP Base and Foundation models, and Juno support) updated topic from Qualcomm LT (ifc6410 board support) updated topic from HiSilicon LT (Hi36xx, HiP04, and X5HD2 families support) updated LLVM topic (the community llvmlinux-latest branch) included ILP32 patch set v3 rebased onto 3.19. Initial tests using syscalls LTP tests done. When using ILP32 userland, a few tests have to be skipped (msgctl07, msgrcv0[1-7], msgsnd01) to avoid the stalls, […]

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Spark Electron Cellular Module for M2M Projects Comes with a $3 Monthly Data Plan (Crowdfunding)

Spark IO started with Spark Core, a tiny Wi-Fi module, followed with Spark Photon is a cheaper, faster, and tinier Wi-Fi module, and now the company is launching Spark Electron to bring cellular connectivity to hobbyist projects at an affordable cost and small form factor. Spark Electron specifications: MCU – ST Micro STM32F205 ARM Cortex M3 microcontroller @ 120 MHz with  1MB Flash, 128K RAM Cellular Connectivity – U-Blox SARA U-series (3G) or G-series (2G) modem + NanoSIM card slot + u.FL connector for Antenna Headers – 36 pins with 28 GPIOs (D0-D13, A0-A13), plus TX/RX, 2 GNDs, VIN, VBAT, WKP, 3V3, RST USB – micro USB port for power and programming Misc – Setup and reset buttons, LED Dimensions – 5.08 cm x 2.03 cm x 0.76 cm (1.27 cm including headers) The board can be programmed with Wiring (Arduino’s programming language), C/C++, or ARM assembly. It’s longer than Spark […]

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GroBotz Interactive Robot Project is Made of Easy to Assemble Smart Blocks (Crowdfunding)

GroBotz makes me think of Lego applied to robotics. The project consists of modules such as motors, sensors, buttons, switches, or cameras that snap together in order to create a robot on wheels, games, toys, a musical instrument, or whatever idea you may have, and the hardware is then programmed using a graphical user interface. A Raspberry Pi board is used for the brain of the robot, and Microchip PIC MCUs for the smart blocks. The software is programmed in C# using Xamarin, the user interface is based on Unity, OpenCV is used for image processing, and during development a plastic part where printed with Makerbot, and schematics and PCB layout designed with CadSoft EAGLE. The company has now come up with a number of modules as shown in the picture below. Your robot can then be controlled over Wi-Fi with GroBotz app which works on Windows, Mac OS, iOs, […]

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Freescale Announces i.MX 6SoloX ARM Cortex A9 & Cortex M4 Processor

Freescale i.MX6 SoloX processor started to show up in the ARM Linux Kernel mailing list last year, and Cortex A9 + Cortex M4 processor showed up in some marketing documents, but so far all documentation was tied to a non-diclosure agreement. However, all resources are now publicly available, as the company officially launched i.MX 6SoloX processor at Embedded World 2015. Freescale i.MX 6SoloX specifications: CPU – ARM Cortex-A9 up to 1 GHz with 512 KB L2 cache, 32 KB instruction and data caches and NEON SIMD media accelerator MCU – ARM Cortex-M4 up to 200 MHz with 16 KB instruction and data caches, 64 KB TCM, MPU and FPU Memory Interface 16/32-bit DDR3-800 and DDR3L-800, 16/32-bit LPDDR2-800 SLC/MLC NAND, 62-bit ECC, ONFI2.2 2x DDR Quad SPI NOR flash, 16/32-bit NOR Flash Display and Camera Interfaces Parallel RGB LVDS 20-bit parallel CMOS sensor interface NTSC/PAL analog video input interface Multimedia GPU […]

Rockchip RK3568, RK3588 and Intel x86 SBCs and SoMs in 2025
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Freescale Kinetis based Mbed IoT Starter Kit Ethernet Edition Connects to IBM IoT Cloud

ARM, IBM and Freescale have jointly announced Mbed IoT Start Kit – Ethernet Edition at Embedded World 2015 that consists of  a Freescale Kinetis Cortex M4 mbed-enabled development board and a sensor IO application shield that interface with IBM Bluemix cloud platform. Freescale FRDM-K64F Freedom development board specifications: MCU – Freescale Kinetis K64 (MK64FN1M0VLL12) ARM Cortex M4 MCU @ 120 MHz with 1 MB flash memory, 256 KB RAM External Storage – SDHC slot Connectivity – 10/100M Ethernet USB – Dual role USB interface with micro-B USB connector Sensors – FXOS8700CQ accelerometer and magnetometer Headers – Arduino R3 compatible I/O connectors Misc – RGB LED, two user push buttons Power Supply – OpenSDAv2 USB, Kinetis K64 USB, and external source The board also features a programmable OpenSDAv2 debug circuit supporting the CMSIS-DAP Interface software that provides a mass storage device (MSD) flash programming interface, or a CMSIS-DAP debug interface, or […]

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ARM Releases Kernel Drivers for Mali-T880 / T860 GPUs, User Space Drivers for Mali-T76x GPUs

ARM Mali GPU drivers includes both open source kernel drivers, and binary userspace drivers supporting framebuffer and/ior X11 implementation. The former is rarely an issue and is quickly released, but the latter requires porting and testing for a specific hardware platform, as well legal work, which greatly delay the releases. Mali-T880 GPU was announced at the beginning of the month together with ARM Cortex A72, and on February 17, 2015, ARM released an update to their Mali-T600 series, Mali-T700 series & Mali-T860/T880 GPU kernel device drivers with revision r5p1-00rel0 that adds supports to Mali-T860 and Mali-T880 GPU. These open source drivers are available for Android and Linux, and also support early Mali-T700 and T600 GPUs. Separately, the company has also released Mali-T76X GPU drivers for Firefly board powered by Rockchip RK3288 quad core Cortex A17 processor featuring a Mali-T764 GPU. The first release only supports the framebuffer driver, but ARM […]

Boardcon CM3588 Rockchip RK3588 System-on-Module designed for AI and IoT applications