Linux 4.18 Release – Main Changes, Arm and MIPS Architecture

Linux Changelog 4.18

Linus Torvalds has just announced the release of Linux 4.18: One week late(r) and here we are – 4.18 is out there. It was a very calm week, and arguably I could just have released on schedule last week, but we did have some minor updates. Mostly networking, but some vfs race fixes (mentioned in the rc8 announment as “pending”) and a couple of driver fixes (scsi, networking, i2c). Some other minor random things (arm crypto fix, parisc memory ordering fix). Shortlog appended for the (few) details. Some of these I was almost ready to just delay to until the next merge window, but they were marked for stable anyway, so it would just have caused more backporting. The vfs fixes are for old races that  are really hard to hit (which is obviously why they are old and weren’t noticed earlier). Some of them _have_ been seen in real life, some of them probably need explicit help to ever …

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Congatec conga-SMX8 is a SMARC 2.0 Module Based on NXP i.MX8 Processor

We’ve already seen some SMARC 2.0 SoM based on NXP i.MX8 processor with for instance, i.MX 8M based SECO SM-C12. We now have at more choice thanks to Congatec which just announced  conga-SMX8, the company’s first SMARC 2.0 Computer-on-Module based on the NXP i.MX8 Arm Cortex-A53/A72 processor. conga-SMX8 SoM specifications: SoC (one or the other) NXP i.MX8 Quad Max with 2x Arm Cortex-A72, 4x Arm Cortex-A53, 2x Arm Cortex-M4F, 2x Vivante GC7000XSVX GPU NXP i.MX8 QuadPlus with 1x Arm Cortex-A72, 4x Arm Cortex-A53, 2x Arm Cortex-M4F, 2x Vivante GC7000Lite/XSVX GPU NXP i.MX8 DualMax with 2x Arm Cortex-A72, 2x Arm Cortex-M4F, 2x Vivante GC7000Lite/XSVX GPU System Memory – Up to 8 GB LPDDR4 memory | 3200 MT/s Storage – Up to 64GB eMMC flash, micro SD 3.0 card socket Other On-Module Chips 2x Gigabit Ethernet transceiver Optional M.2 1216 WiFi module (soldered down) USB hub 314-pin MXM Edge connector with Storage – 1x SATA III Networking – 2x Gbit Ethernet Video …

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Google Unveils Edge TPU Low Power Machine Learning Chip, AIY Edge TPU Development Board and Accelerator

AIY Edge TPU Dev Board

Google introduced artificial intelligence and machine learning concepts to hundreds of thousands of people with their AIY projects kit such as the AIY Voice Kit with voice recognition and the AIY Vision Kit for computer vision applications. The company has now gone further by unveiling Edge TPU, its own  purpose-built ASIC chip designed to run TensorFlow Lite ML models at the edge, as well as corresponding AIY Edge TPU development board, and AIY Edge TPU accelerator USB stick to add to any USB compatible hardware. Google Edge TPU (Tensor Processing Unit) & Cloud IoT Edge Software Edge TPU is a tiny chip for machine learning (ML) optimized for performance-per-watt and performance-per-dollar.  It can either accelerate ML inferencing on device, or can pair with Google Cloud to create a full cloud-to-edge ML stack. In either case, local processing reduces latency, remove the needs for a persistent network connection, increases privacy, and allows for higher performance using less power. The chip will …

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SECO Q7-C25 / Q7-C26 QSeven SoMs Feature NXP i.MX 8M / i.MX 8Quad Processor

We’ve previously covered SECO’s SM-C12 SMARC 2.0 i.MX 8M system-on-module, but the company has just unveiled two new module families which are compliant with Qseven – another SoM standard – and powered by NXP i.MX 8M dual/quad core Cortex A53 processor and NXP i.MX 8Quad Cortex A53 or A72/A53 SoC with respectively Q7-C25 and Q7-C26 systems-on-module. SECO Qseven i.MX 8/8M System-on-Module Q7-C25 / Q7-C26 specifications: SoC Q7-C25 (one or the other) NXP i.MX 8M Quad 4x Cortex-A53 cores up to 1.5GHz, 1x Cortex-M4 F real-time core, Vivante GC7000Lite GPU, VPU NXP i.MX 8M Dual 2x Cortex-A53 cores up to 1.5GHz, 1x Cortex-M4 F real-time core, Vivante GC7000Lite GPU, VPU NXP i.MX 8M QuadLite 4x Cortex-A53 cores up to 1.5GHz, , 1x Cortex-M4 F real-time core, Vivante GC7000Lite GPU no VPU Q7-C26 (one or the other) NXP i.MX 8QuadMax 2x Cortex-A72 cores + 4x Cortex-A53 cores + 2x Cortex-M4F cores, 2x Vivante GC7000XSVX GPUs NXP i.MX 8QuadPlus 1x Cortex-A72 cores + 4x …

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Visual Studio 2017 with an Embedded Linux Arm Device

This is a non-sponsored guest post written by Marc Goodner: Principal Program Manager, Microsoft, and Jeremias Cordoba: Innovation Engineer, Toradex. Today many embedded devices run some flavor of Linux as their primary operating system. This poses a challenge to developers who run Windows on their development machine. This article explains a new way to use the latest Visual Studio for C++ development on an embedded Arm Devices from a Windows Host PC using containers for the build environment. The device we are deploying to is from the Toradex Colibri Family of System on Modules using the NXP i.MX 6ULL SoC, which features an Arm Cortex A-7. As a demo project we will connect a Bluetooth Sensor with the Toradex Colibri Module. Please note that Visual Studio support for this case is in an early state, you will see improvements from Microsoft and Toradex in the coming months. Prerequisites Colibri i.MX 6ULL with Wi-Fi/BT and an Aster Carrier Board TI SensorTag (Bluetooth low energy) …

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VisionSOM-RT is an Industrial System-on-Module based on NXP i.MX RT Arm Cortex-M7 Processor

VisionSOM-RT NXP i.MX RT SoM

It’s hard to keep up with all the systems-on-module based on Arm Cortex-A “application class” processors, but so far I can’t remember seeing any Arm Cortex-M “microcontroller class” SoM. However, SoMLabs is currently working on VisionSOM-RT, a system-on-module based on NXP i.MX RT 1050 Arm Cortex-M7 processor clocked at 600 MHz. NXP i.MX RT series processors are actually promoted as a “crossover” processor delivering application processor performance with real-time capabilities right at the edge between the two classes of processors. VisionSOM-RT (SLS12Rx) module preliminary specifications: SoC- NXP i.MX RT Arm Cortex-M7 processor @ up to 600MHz with NXP PXP 2D graphics accelerator, and Graphics Engine PXP PiXel processing pipeline for imagine resize, rotation, overlay and color space conversion. Memory – 512kB on-chip RAM memory, up to 32MB SDRAM Storage – Up to 16MB QuadSPI flash, optional 4GB eMMC flash 200-pin SO-DIMM edge connector with Display Interface – 8/16/24-bit Parallel RGB up to 1366 x 768 (WXGA) Networking – 10/100Mbit/s Ethernet …

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Linux 4.17 Release – Main Changes, Arm & MIPS Architectures

Linus Torvalds released Linux 4.17 last Sunday: So this last week was pretty calm, even if the pattern of most of the stuff coming in on a Friday made it feel less so as the weekend approached. And while I would have liked even less changes, I really didn’t get the feeling that another week would help the release in any way, so here we are, with 4.17 released. No, I didn’t call it 5.0, even though all the git object count numerology was in place for that. It will happen in the not _too_distant future, and I’m told all the release scripts on kernel.org are ready for it, but I didn’t feel there was any real reason for it. I suspect that around 4.20 – which is I run out of fingers and toes to keep track of minor releases, and thus start getting mightily confused – I’ll switch over. That was what happened for 4.0, after all. As …

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Toradex Launches Apalis iMX8 Computer-on-Module based on NXP i.MX 8QuadMax SoC

Toradex-Apalis-i.MX8-SoM

Toradex Apalis iMX8 is another system-on-module powered by NXP i.MX 8QuadMax hexa core Arm Cortex A72 + 53 processor, which comes with 4GB LPDDR4 RAM, up to 16GB flash, and an on-board dual-band 802.11ac 2×2 MU-MIMO Wi-Fi and Bluetooth 5 ready module. The company has just opened early access for selected customers, so it has become possible to start developing products with the MXM3 computer-on-module. Apalix i.MX8 module specifications: SoC – NXP i.MX 8QuadMax hexa core processor with 2x Arm Cortex-A72 cores @ 1.6 GHz, 4x Arm Cortex-A53 cores @ 1.26 GHz, 2x Cortex-M4 real-time core @ 266 MHz, and dual Vivante GC7000XSVX GPU System Memory – 4GB LPDDR4 (64 Bit) Storage – Up to 16GB eMMC flash On-module Connectivity Gigabit Ethernet via Microchip KSZ9031 transceiver with low power features Dual-band 802.11ac 2×2 MU-MIMO Wi-Fi and Bluetooth 5 via Azurewave AW-CM276NF M.2 1216 LGA module Audio – NXP SGTL5000 low power stereo codec 314-pim MXM3 edge connector with: Storage – …

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