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Hardware

LTE-equipped machine vision system runs Linux on a Jetson TX2

Filed under
Linux
Hardware

Imago’s “VisionBox Daytona” machine vision computer runs Linux on a Jetson TX2 and offers 4G LTE plus dual GbE camera ports with PoE and triggers. Other recent, Linux-based Imago systems include an octa-core VisionBox Le Mans and an EdgeBox cloud server.

Imago Technologies has released a variety of Linux-ready VisionBox machine vision systems in recent years running on both Arm and x86 processors (see farther below). Now, it has introduced an Arm-based VisionBox Daytona computer that answers the question: What do you do when your remote machine-vision computer needs a little help? Unlike many vision computers, the VisionBox adds LTE so that “questionable decisions” can be remotely “validated by the expert through image analysis,” says Imago.

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Also: 'Austin Beach': Intel's Compute Element Fanless NUC

Linux Devices/Embedded: Tachyum, AAEON, 'Home Assistant', Penguin Watch and RISC-V

Filed under
Linux
Hardware
  • Tachyum Successfully Deploys Linux OS on Universal Processor Chip

    Tachyum Inc. announced today it has successfully deployed the Linux OS on its Prodigy Universal Processor architecture...

  • New HERO SDK Reduces Workload of Developers Utilizing Linux Operating Systems

    AAEON, a leader in industrial embedded solutions, announces the new HERO SDK for Linux. This innovative toolkit makes hardware control and monitoring a snap, speeding up deployment and time-to-market for developers who choose Linux based platforms for their applications.

    HERO SDK helps to reduce the workload of developers utilizing Linux operating systems and make utilizing AAEON hardware in their projects easier. By integrating our innovative API within the BIOS on AAEON boards and systems, the HERO SDK libraries are able to move hardware control out of the Linux kernel and onto the BIOS, eliminating the need for drivers which require configuration or limit your choice in OS. This provides developers with unparalleled freedom and flexibility in utilizing their preferred Linux OS, and eliminates the guesswork in downloading and installing drivers.

  • More Yak Shaving: Moving to nftables to secure Home Assistant

    When I setup Home Assistant last year one of my niggles was that it wanted an entire subdomain, rather than being able to live under a subdirectory. I had a desire to stick various things behind a single SSL host on my home network (my UniFi controller is the other main one), rather than having to mess about with either SSL proxies in every container running a service, or a bunch of separate host names (in particular one for the backend and one for the SSL certificate, for each service) in order to proxy in a single host.

  • Penguin Watch — Pi Zeros and Camera Modules in the Antarctic

    Penguin Lifelines was a programme run by the Zoological Society of London, crowdsourcing the tracking of penguin colonies in Antarctica. It’s since evolved into something called Penguin Watch, now working with the World Wildlife Fund (WWF) and British Antarctic Survey (BAS). It’s citizen science on a big scale: thousands of people from all over the world come together on the internet to…click on penguins. By counting the birds in their colonies, users help penguinologists measure changes in the birds’ behaviour and habitat, and in the larger ecosystem, thus assisting in their conservation.

  • Companies Pushing Open Source RISC-V Silicon Out to the Edge

    It emerged as a force in the silicon market last year, and its been gaining momentum ever since.

Running Deep Learning Models On Intel Hardware? It's Time To Consider A Different OS

Filed under
GNU
Linux
Server
Hardware

Firstly, Intel has done extensive work to make the Xeon family of processors highly optimized for AI. The Intel Xeon Scalable processors outsmart GPUs in accelerating the training on large datasets.

Intel is telling its customers that they don’t need expensive GPUs until they meet a threshold. Most of the deep learning training can be effectively done on CPUs that cost a fraction of their GPU counterparts.

Beyond the marketing messages and claims, Intel went onto prove that their deep learning stack performs better than NVIDIA GPU-based stack. Recently, Intel published a benchmark to show its leadership in deep learning. Intel Xeon Scalable processers trained a deep learning network with 7878 images per second on ResNet-50 outperforming 7844 images per second on NVIDIA Tesla V100.

Intel’s performance optimization doesn’t come just from its CPUs. It is delivered by a purpose-built software stack that is highly optimized at various levels. From the operating system to the TensorFlow framework, Intel has tweaked multiple layers of software to deliver unmatched performance.

To ease the process of running this end-to-end stack, Intel has turned to one of its open source projects called Clear Linux OS. Clear Linux project was started as a purpose-built, container-optimized, and lightweight operating system. It was started with the premise that the OS running a container doesn’t need to perform all the functions of a traditional OS. Container Linux, the OS developed by CoreOS (now a part of Red Hat) followed the same philosophy.

Within a short span, Clear Linux gained popularity among open source developers. Intel kept improving the OS, making it relevant to run modern workloads such as machine learning training jobs, AI inferencing, analytics and edge computing.

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Also: Intel Core i9 9900KS Allowing 5.0GHz All-Core, Icelake News Coming This Week

Open Hardware: Adafruit Feather and Stanford Doggo

Filed under
Hardware
OSS
  • Feather Plus Blackberry Equals Open Source Fauxberry

    The keyboard is a superior means of input, but to date no one has really figured out how to make a keyboard for small, handheld electronics. You could use tact switches, but that’s annoying, or you could use a touch screen. The best option we’ve seen is actually a Blackberry keyboard, and [arturo182] has the best example yet. It’s a small handheld device with a screen, keyboard, and WiFi that’s ready to do anything imaginable. Think of it as an Open Source Fauxberry. In any case, we want it.

    This project is actually a breakout board of sorts for the Adafruit Feather system, and therefore has support for WiFi, cellular, or pretty much any other networking of connectivity. To this blank canvas, [arturo] added an accelerator/magnetometer sensor, a single Neopixel, and of course the beautiful Blackberry keyboard. This keyboard is attached to an ATSAMD20G, a microcontroller with a whole bunch of I/O that translates key presses into I2C for the Feather.

  • Students from Stanford's Robotics Club Releases Open-Source Robo-Dog Online

    Robotics isn't cheap by any means, and no one knows this better than the students of the Extreme Mobility Team of Standford University's Robotics Club (SEMT). The materials used by university robotics clubs can cost upwards of tens of thousands of dollars, making it that much harder for many high schools and less well-funded colleges and universities to invest heavily in this important field of research.

  • Watch this open-source dog robot do backflips [Ed: This is more likely to be used in military rather than in aeronautics and astronautics (luxury of the rich)]

    “We’re hoping to provide a baseline system that anyone could build,” says Patrick Slade, graduate student in aeronautics and astronautics and mentor for Extreme Mobility.

  • Meet Doggo: Stanford’s cute open-source four-legged robot

    Doggo follows similar designs to other small quadrupedal robots, but what makes it unique is its low cost and accessibility. While comparable bots can cost tens of thousands of dollars, the creators of Doggo — Stanford’s Extreme Mobility lab — estimate its total cost to be less than $3,000. What’s more, the design is completely open source, meaning anyone can print off the plans and assemble a Doggo of their very own.

  • Stanford Students Built This Adorable, Bouncy, Open-Source Robot Dog

    Nearly all of the parts used to create Doggo were bought intact through the internet, while the rest can be easily 3D-printed. The total costs involved in building Doggo—including shipping and handling—amounted to less than $3,000, Kau and his team claim. Via the website Github, the team has also released all of the relevant information you would need to create your Doggo, including software coding, supply list, and manual instructions. From there, any enterprising roboticist could tweak the design to create an even more capable Doggo.

More HDR Display Bits On The Way For The Linux 5.3 Kernel

Filed under
Linux
Hardware

For years there have been open-source developers working on plumbing support for High Dynamic Range (HDR) displays into the Linux desktop stack and it looks like the Direct Rendering Manager driver support is slowly but surely getting there.

With the Linux 5.3 kernel cycle later this summer, there will be more HDR infrastructure support in place. As part of this week's drm-misc-next pull request to DRM-Next for staging this Linux 5.3 material there are more HDR pieces.

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AMD Staging Another Fix To Try Correcting Some Raven Ridge Systems On Linux

Filed under
Linux
Hardware

AMD Raven Ridge APUs have been out for more than one year now and at least under Linux can still be quite problematic depending upon the particular motherboard BIOS and other factors. Fortunately, while Raven 2 and Picasso APU support is appearing to be in better shape, the AMD open-source developers haven't forgot about these problematic Raven 1 systems.

Out today is the latest patch trying to help those with original Raven Ridge systems. This latest hopeful fix is now skipping over loading the DMCU firmware for Raven Ridge. DMCU in this context is the Display Micro-Controller Unit and is the micro-controller used for Panel Self Refresh (PSR) and similar functionality.

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Also: Intel 19.20.13008 Open-Source Compute Stack Restores Broadwell To Production Quality

Performance Impact of Serious CPU Defects

Filed under
Graphics/Benchmarks
Hardware
Security

4 New Arduino Nano Boards Are Here: More Powerful Than Before

Filed under
Linux
Hardware

The open source Arduino Project was started long back in 2003 as a program for students to help them tinker with sensors and their applications without spending tons of money. Over the course of time, this open source platform evolved and facilitated the launch of various versions of the Arduino hardware.

Adding another chapter to Arduino’s hardware journey, the Italian boardmakers have announced the launch of four new products that will remind you of the classic Arduino Nano 3. The 4 Arduino product in the lineup serve different purposes, so let’s briefly tell you about them:

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Direct: What’s new at Maker Faire Bay Area 2019

Louis-Philippe Véronneau: Am I Fomu ?

Filed under
Linux
Hardware

A few months ago at FOSDEM 2019 I got my hands on a pre-production version of the Fomu, a tiny open-hardware FPGA board that fits in your USB port. Building on the smash hit of the Tomu, the Fomu uses an ICE40UP5K FPGA instead of an ARM core.

I've never really been into hardware hacking, and much like hacking on the Linux kernel, messing with wires and soldering PCB boards always intimidated me. From my perspective, playing around with the Fomu looked like a nice way to test the water without drowning in it.

Since the bootloader wasn't written at the time, when I first got my Fomu hacker board there was no easy way to test if the board was working. Lucky for me, Giovanni Mascellani was around and flashed a test program on it using his Raspberry Pi and a bunch of hardware probes. I was really impressed by the feat, but it also seemed easy enough that I could do it.

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Also: ItsyBitsy Snek — snek on the Adafruit ItsyBitsy

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