QuickFeather Board is Powered by QuickLogic EOS S3 Cortex-M4F MCU with embedded FPGA (Crowdfunding)

QuickLogic EOS S3 Development Board

Yesterday, I wrote about what I felt what a pretty unique board: Evo M51 board following Adafruit Feather form factor, and equipped with an Atmel SAMD51 Cortex-M4F MCU and an Intel MAX 10 FPGA. But less than 24 hours later, I’ve come across another Adafruit Feather-sized Cortex-M4F board with FPGA fabric. But instead of using a two-chip solution, QuickLogic QuickFeather board leverages the company’s EOS S3 SoC with a low-power Cortex-M4F core and embedded FPGA fabric. QuickFeather specifications: SoC – QuickLogic EOS S3 with Arm Cortex-M4F Microcontroller @ up to 80 MHz and 512 Kb SRAM, plus an embedded FPGA (eFPGA) with 2400 effective logic cells and 64Kb RAM Storage – 16Mbit SPI NOR flash USB – Micro USB  port with data signals tied to eFPGA programmable logic Sensors – Accelerometer, pressure sensor, built-in PDM microphone Expansion I/Os – Breadboard-compatible 0.1″ (2.54 mm) pitch headers including 20 Feather-defined GPIO + 13 additional GPIO with UART, I2C, I2S and SPI Debugging …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Bamboo Systems B1000N 1U Server Features up to 128 64-bit Arm Cores, 512GB RAM

Bamboo Systems B1000N Arm Server

SolidRun CEx7-LX2160A COM Express module with NXP LX2160A 16-core Arm Cortex A72 processor has been found in the company’s Janux GS31 Edge AI server in combination with several Gyrfalcon AI accelerators. But now another company – Bamboo Systems – has now launched its own servers based on up to eight CEx7-LX2160A module providing 128 Arm Cortex-A72 cores, support for up to 512GB DDR4 ECC, up to 64TB NVMe SSD storage, and delivering a maximum of 160Gb/s network bandwidth in a single rack unit. Bamboo Systems B1000N Server specifications: B1004N – 1 Blade System B1008N – 2 Blade System N series Blade with 4x compute nodes each (i.e. 4x CEx7 LX2160A COM Express modules) Compute Node – NXP 2160A 16-core Cortex-A72 processor for a total of  64 cores per blade. Memory – Up to 64GB ECC DDR4 per compute node or 256GB per blade. Storage – 1x 2.5” NVMe SSD PCIe up to 8TB per compute node, or 32TB per blade …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Register to the Embedded Online Conference for Free Before February 29th

Embedded Online Conference

Events such as the Embedded Linux Conference and Embedded Systems Conference take place in the US and Europe every year. There are plenty of talks and it’s certainly good for networking, but you need to travel to the event and the entrance fee to have access to all session costs several hundred dollars if you book early, and over one thousand dollars if you register close to the date of the event. Most ELC/ELCE videos usually end up on The Linux Foundation YouTube channel, but the Beningo Embedded Group and Embedded Related website decided to organize a similar conference happening online and simply called the “Embedded Online Conference“. The conference offers topics about embedded systems, DSP, machine learning and FPGA and will take place on May 20.  There are currently 17 talks, but they are still calling for talks so more sessions may be added before the actual event. You’ll also be able to ask questions to the speakers. Some …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Toradex AI Embedded Vision Starter Kit Leverages Amazon Web Services for AI and ML Applications

Toradex AI Embedded Vision AWS Starter Kit

Toradex, Amazon Web Services (AWS), and NXP Semiconductors collaborated to create the AI Embedded Vision Starter Kit aiming to ease the development of cloud-connected computer vision and machine learning applications in industries such as industrial automation, agriculture, medical equipment, and many more. The AI Embedded Vision Starter Kit includes the following items: Toradex Apalis iMX8 System on Module (SoM) powered by NXP i.MX 8QuadMax applications processor Toradex Ixora Carrier Board Allied Vision Alvium 1500 industrial-grade MIPI CSI-2 camera All required cables and a 12VDC (30W) power supply Full software stack, including source code for running the device as well as for cloud deployment Extensive documentation 50 USD AWS credit The kit will help developers meet the must-have requirements of smart connected devices including secure connectivity, remote monitoring, OTA updates, maximum uptime & reliability, compact form factor, cost-optimized hardware, computer vision and machine learning algorithms optimized for low-power hardware, and more. Alex Dopplinger, industrial marketing manager at NXP explains The step-by-step …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Arm Introduces Ethos NPU Family, Mali-G57 GPU, and Mali-D37 Display Processor

Arm Ethos NPU: Ethos-M37, Ethos-N57 & Ethos-N77

Arm has just announced four new IP solutions with the most interesting being Ethos NPU (Neural Processing Unit) family with both Ethos-N57 and Ethos-N37 NPUs for mainstream devices, but the company also announced the new Arm Mali-G57, the first mainstream Valhall GPU, as well as Arm Mali-D37 DPU (Display Processing Unit) for full HD and 2K resolution. Arm Ethos NPU Family There are three members of the new Ethos family, and if you’ve never heard about Ethos-N77 previously, that’s because it was known as Arm ML processor. The three NPU’s cater to different AI workloads / price-point from 1 TOPS to 4 TOPS: Ethos-N37 Optimized for 1 TOP/s ML performance range 512 8×8 MAC/cycle 512KB internal memory Small footprint (<1mm2) For smart cameras, entry smartphones, DTV Ethos-N57 Optimized for 2 TOP/s ML performance range 1024 8×8 MAC/cycle 512KB internal memory For mainstream smartphones, smart home hubs Ethos-N77 Up to 4 TOP/s 2048 8×8 MAC/cycle 1-4 MB internal memory For computational …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Intrinsyc Unveils Open-Q 845 µSOM and Snapdragon 845 Mini-ITX Development Kit

Open-Q 845 µSOM Development Kit

Intrinsyc introduced the first Qualcomm Snapdragon 845 hardware development platform last year with its Open-Q 845 HDK designed for OEMs and device makers. But the company has now just announced a solution for embedded systems and Internet of Things (IoT) products with Open-Q 845 micro system-on-module (µSOM) powered by the Snapdragon 845 octa-core processor, as well as a complete development kit featuring the module and a Mini-ITX baseboard. Open-Q845 µSOM Specifications: SoC – Qualcomm Snapdragon SDA845 octa-core processor with 4x Kryo 385 Gold cores @ 2.649GHz + 4x Kryo 385 Silver low-power cores @ 1.766GHz cores, Hexagon  685 DSP, Adreno 630 GPU with OpenGL ES 3.2 + AEP (Android Extension Pack),  DX next, Vulkan 2, OpenCL 2.0 full profile System Memory – 4GB or 6GB dual-channel high-speed LPDDR4X SDRAM at 1866MHz Storage – 32GB or 64GB UFS Flash Storage Connectivity Wi-Fi 5 802.11a/b/g/n/ac 2.4/5Ghz 2×2 MU-MIMO (WCN3990) with 5 GHz external PA & U.FL antenna connector Bluetooth 5.x Audio & …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Embedded Linux Conference (ELC) Europe 2019 Schedule – October 28-30

Embedded Linux Conference Europe 2019 Schedule

I may have just written about Linaro Connect San Diego 2019 schedule, but there’s another interesting event that will also take place this fall: the Embedded Linux Conference Europe on  October 28 -30, 2019 in Lyon, France. The full schedule was also published by the Linux Foundation a few days ago, so I’ll create a virtual schedule to see what interesting topics will be addressed during the 3-day event. Monday, October 28 11:30 – 12:05 – Debian and Yocto Project-Based Long-Term Maintenance Approaches for Embedded Products by Kazuhiro Hayashi, Toshiba & Jan Kiszka, Siemens AG In industrial products, 10+ years maintenance is required, including security fixes, reproducible builds, and continuous system updates. Selecting appropriate base systems and tools is necessary for efficient product development. Debian has been applied to industrial products because of its stability, long-term supports, and powerful tools for packages development. The CIP Project, which provides scalable and customizable base image and BSP layers, is now used in …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Arm Techcon 2019 Schedule – Machine Learning, Security, Containers, and More

Arm Techcon 2019

Arm TechCon will take place on October 8-10, 2019 at San Jose Convention Center to showcase new solutions from Arm and third-parties, and the company has now published the agenda/schedule for the event. There are many sessions and even if you’re not going to happen it’s always useful to checkout what will be discussed to learn more about what’s going on currently and what will be the focus in the near future for Arm development. Several sessions normally occur at the same time, so as usual I’ll make my own virtual schedule with the ones I find most relevant. Tuesday, October 8  09:00 – 09:50 – Open Source ML is rapidly advancing. How can you benefit? by Markus Levy, Director of AI and Machine Learning Technologies, NXP Over the last two years and still continuing, machine learning applications have benefited tremendously from the growing number of open source frameworks, tools, and libraries to support edge inferencing. These include CMSIS-NN, ARM …

Support CNX Software – Donate via PayPal or become a Patron on Patreon