arm News - Page 42 of 84 - CNX Software

August 27, 2017June 18, 2018 by Jean-Luc Aufranc (CNXSoft) - 4 Comments

Embedded Linux Conference & Open Source Summit Europe 2017 Schedule

The Embedded Linux Conference & IoT summit 2017 took place in the US earlier this year in February, but there will soon be a similar event with the Embedded Linux Conference *& Open Source Summit Europe 2017 to take up in Europe on October 23 – 25 in Prague, Czech Republic, and the Linux Foundation has just published the schedule. It’s always useful to find out what is being discussed during such events, even if you are not going to attend, so I went through the different sessions, and compose my own virtual schedule with some of the ones I find the most interesting. Monday, October 23 11:15 – 11:55 – An Introduction to SPI-NOR Subsystem – Vignesh Raghavendra, Texas Instruments India Modern day embedded systems have dedicated SPI controllers to support NOR flashes. They have many hardware level features to increase the ease and efficiency of accessing SPI NOR […]

August 14, 2017August 14, 2017 by Jean-Luc Aufranc (CNXSoft) - 33 Comments

Fedora 26 Supports Single “Unified” OS Images for Multiple ARM Platforms

The decision to use device tree in Linux occurred several years ago, after Linus Torvalds complained that Linux on ARM was a mess, with the ultimate goal of providing a unified ARM kernel for all hardware. Most machine specific board files in arch/arm/mach-xxx/ are now gone from the Linux kernel, being replaced by device tree files, and in many case you simply need to replace the DTB (Device Tree Binary) file from an operating system to run on different hardware platforms. However, this is not always that easy as U-boot still often differ between boards / devices, so it’s quite frequent to distribute different firmware / OS images per board. Fedora has taken another approach, as the developers are instead distributing a single Fedora 26 OS ARMv7 image, together with an installation script. Images for 64-bit ARM (Aarch64) are a little different since they are designed for SBSA compliant servers, so […]

August 9, 2017August 9, 2017 by Jean-Luc Aufranc (CNXSoft) - 16 Comments

Movidius Neural Compute Stick Shown to Boost Deep Learning Performance by about 3 Times on Raspberry Pi 3 Board

Intel recently launched Movidius Neural Compute Stick (MvNCS)for low power USB based deep learning applications such as object recognition, and after some initial confusions, we could confirm the Neural stick could also be used on ARM based platforms such as the Raspberry Pi 3. Kochi Nakamura, who wrote the code for GPU accelerated object recognition on the Raspberry Pi 3 board, got hold of one sample in order to compare the performance between GPU and MvNCS acceleration. His first attempt was quite confusing as with GoogLeNet, Raspberry Pi 3 + MvNCS achieved an average inference time of about 560ms, against 320 ms while using VideoCore IV GPU in RPi3 board. But then it was discovered that the “stream_infer.py” demo would only use one core out of the 12 VLIW 128-bit vector SHAVE processors in Intel’s Movidius Myriad 2 VPU, and after enabling all those 12 cores instead of just one, […]

August 7, 2017 by Jean-Luc Aufranc (CNXSoft) - 36 Comments

How ARM Nerfed NEON Permute Instructions in ARMv8

This is a guest post by blu about an issue he found with a specific instruction in ARMv8 NEON. He previously wrote an article about OpenGL ES development on Ubuntu Touch, and one or two other posts. This is not a happy-ending story. But as with most unhappy-ending stories, this is a story with certain moral for the reader. So read on if you appreciate a good moral. Once upon a time there was a very well-devised SIMD instruction set. Its name was NEON, or formally — ARM Advanced SIMD — ASIMD for short (most people still called it NEON). It was so nice, that veteran coders versed in multiple SIMD ISAs often wished other SIMD ISAs were more like NEON. NEON had originated as part of the larger ARM ISA version 7, or ARMv7, for short. After much success in the mobile and embedded domains, ARMv7 was superseded by […]

August 4, 2017August 4, 2017 by Jean-Luc Aufranc (CNXSoft) - 1 Comment

Mediatek MT2625 NB-IoT SoC is Designed for Cellular IoT Devices working Worldwide

Mediatek has recently unveiled MT2625 SoC based on an ARM Cortex-M core, equipped with an NB-IoT “WorldMode” modem allowing for a single design worldwide, and supporting the latest 3GPP Release 14 (LTE Cat NB2) specification. Mediatek MT2625 specifications: CPU – ARM Cortex-M @ up to 104 MHz with FPU Embedded Memory – 4MB PSRAM Storage – 4MB NOR Flash Connectivity NB-IoT compatible with 3GPP Release 14 Full frequency band (450MHz to 2.1GHz) of 3GPP R13 (NB1) and R14 (NB2) standards Integrated baseband, RF, and modem DSP Peripherals – I2C, I2S, PCM, SDIO, UART Power Supply – Integrated PMU The solution will be found in products for worldwide transportation, municipal use, and consumer products, with a much longer battery life compared to existing devices relying on other 2G/3G/4G standards. According to the press release, one of the first module based on MT2625 has been designed in collaboration with China Mobile, integrates […]

August 2, 2017August 2, 2017 by Jean-Luc Aufranc (CNXSoft) - 8 Comments

Intel’s Movidius Neural Compute Stick Supports Raspberry Pi 3 Board

Last month, Intel introduced Movidius Neural Computer Stick to accelerate applications such as object recognition, and do so offline, i.e. without the cloud, and at low power. While there was not that much information available at the time, the minimal requirements for the host machine were that it had to be a x86_64 computer running Ubuntu 16.04, and come with at least 1GB RAM, and 4GB storage. So I understood the stick would only work attached with 64-bit Intel or AMD processors, and ARM development boards would not be an option. But today, I’ve found that Movidius had uploaded a new video showing a Python based object recognition demo with the Neural Compute Stick connected to the the Raspberry Pi 3 board. You just need to add a USB camera, copy ncapi directory from the SDK installed on your Ubuntu 16.04 development machine to the Debian Jessie installed on RPi 3 […]

August 1, 2017 by Jean-Luc Aufranc (CNXSoft) - 1 Comment

Realtek RTL8195AM Ameba WiFi + NFC Module Sells for $9 Shipped

Last year, Realtek Ameba IoT SoCs and development kits launched with boards such as Ameba Arduino, and later, the family got some buzz thanks to $2 RTL8710AF modules like Pine64 Padi IoT stamp, which looked competitive priced against ESP8266 SoC, and featuring an ARM Cortex-M3 core. Back to 2017, ESP8266 appears to still be the preferred platform for makers, and the community around Reatek Ameba processor is relatively small, but maybe the solutions are being integrated into commercial products rather than hobbyists project. Today, as I browsed the web, I noticed that are also some Realtek RTL8195AM module with WiFi, and NFC starting with an “Realtek Ameba-RTL8195AM WiFi & NFC Module” I first found on DFrobot for $15 per unit, but after spending a bit more time searching, I ended finding what looks like the same model for $8.99 including shipping on IC Station. RTL8195AM module (MJIOT-AMB-02) specifications: SoC – […]

July 20, 2017 by Jean-Luc Aufranc (CNXSoft) - 10 Comments

MYiR Introduces Z-Turn Lite Board Powered by Xilinx Zynq-7007S/Zynq-7010 SoC for $69 and Up

Xilinx launched a cost down version of their Zynq-7000 series with Zynq-7000S series SoC combining a single ARM Cortex A9 core with Artix FPGA fabric last year. We’ve already seen sub 100 Euros/Dollars board based on the new SoCs with ZynqBerry and MiniZed boards. MYiR Tech has now launched their own version, a cost-down version of their Z-Turn board, with Z-Turn Lite board featuring either the new cost-down Zynq-7007S or the “good old” Zynq-7010 SoC. Z-Turn Lite specifications: SoC Xilinx XC7Z007S-1CLG400C (Zynq-7007S) with a single ARM Cortex A9 core @ 667 MHz, Artix-7 FPGA fabric with with 23K logic cells, 14,400 LUTs, 66 DSP slices OR Xilinx XC7Z010-1CLG400C (Zynq-7010) with two ARM Cortex A9 cores @ 667 MHz, Artix-7 FPGA fabric with 28K logic cells, 17,600 LUTs, 80 DSP slices. System Memory – 512 MB DDR3 SDRAM (2 x 256MB, 32-bit) Storage – 4GB eMMC flash, 16MB QSPI flash, and […]