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AMD and Linux Kernel

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Linux
Hardware
  • Ataribox runs Linux on AMD chip and will cost at least $250

    Atari released more details about its Ataribox game console today, disclosing for the first time that the machine will run Linux on an Advanced Micro Devices processor and cost $250 to $300.

    In an exclusive interview last week with GamesBeat, Ataribox creator and general manager Feargal Mac (short for Mac Conuladh) said Atari will begin a crowdfunding campaign on Indiegogo this fall and launch the Ataribox in the spring of 2018. The Ataribox will launch with a large back catalog of the publisher’s classic games. The idea is to create a box that makes people feel nostalgic about the past, but it’s also capable of running the independent games they want to play today, like Minecraft or Terraria.

  • Linux 4.14 + ROCm Might End Up Working Out For Kaveri & Carrizo APUs

    It looks like the upstream Linux 4.14 kernel may end up playing nicely with the ROCm OpenCL compute stack, if you are on a Kaveri or Carrizo system.

    While ROCm is promising as AMD's open-source compute stack complete with OpenCL 1.2+ support, its downside is that for now not all of the necessary changes to the Linux kernel drivers, LLVM Clang compiler infrastructure, and other components are yet living in their upstream repositories. So for now it can be a bit hairy to setup ROCm compute on your own system, especially if running a distribution without official ROCm packages. AMD developers are working to get all their changes upstreamed in each of the respective sources, but it's not something that will happen overnight and given the nature of Linux kernel development, etc, is something that will still take months longer to complete.

  • Latest Linux kernel release candidate was a sticky mess

    Linus Torvalds is not noted as having the most even of tempers, but after a weekend spent scuba diving a glitch in the latest Linux kernel release candidate saw the Linux overlord merely label the mess "nasty".

    The release cycle was following its usual cadence when Torvalds announced Linux 4.14 release candidate 2, just after 5:00PM on Sunday, September 24th.

  • Linus Torvalds Announces the Second Release Candidate of Linux Kernel 4.14 LTS

    Development of the Linux 4.14 kernel series continues with the second Release Candidate (RC) milestone, which Linus Torvalds himself announces this past weekend. The update brings more updated drivers and various improvements.

    Linus Torvalds kicked off the development of Linux kernel 4.14 last week when he announced the first Release Candidate, and now the second RC is available packed full of goodies. These include updated networking, GPU, and RDMA drivers, improvements to the x86, ARM, PowerPC, PA-RISC, MIPS, and s390 hardware architectures, various core networking, filesystem, and documentation changes.

More in Tux Machines

Red Hat News/Leftovers

Cloudgizer: An introduction to a new open source web development tool

Cloudgizer is a free open source tool for building web applications. It combines the ease of scripting languages with the performance of C, helping manage the development effort and run-time resources for cloud applications. Cloudgizer works on Red Hat/CentOS Linux with the Apache web server and MariaDB database. It is licensed under Apache License version 2. Read more

James Bottomley on Linux, Containers, and the Leading Edge

It’s no secret that Linux is basically the operating system of containers, and containers are the future of the cloud, says James Bottomley, Distinguished Engineer at IBM Research and Linux kernel developer. Bottomley, who can often be seen at open source events in his signature bow tie, is focused these days on security systems like the Trusted Platform Module and the fundamentals of container technology. Read more

TransmogrifAI From Salesforce

  • Salesforce plans to open-source the technology behind its Einstein machine-learning services
    Salesforce is open-sourcing the method it has developed for using machine-learning techniques at scale — without mixing valuable customer data — in hopes other companies struggling with data science problems can benefit from its work. The company plans to announce Thursday that TransmogrifAI, which is a key part of the Einstein machine-learning services that it believes are the future of its flagship Sales Cloud and related services, will be available for anyone to use in their software-as-a-service applications. Consisting of less than 10 lines of code written on top of the widely used Apache Spark open-source project, it is the result of years of work on training machine-learning models to predict customer behavior without dumping all of that data into a common training ground, said Shubha Nabar, senior director of data science for Salesforce Einstein.
  • Salesforce open-sources TransmogrifAI, the machine learning library that powers Einstein
    Machine learning models — artificial intelligence (AI) that identifies relationships among hundreds, thousands, or even millions of data points — are rarely easy to architect. Data scientists spend weeks and months not only preprocessing the data on which the models are to be trained, but extracting useful features (i.e., the data types) from that data, narrowing down algorithms, and ultimately building (or attempting to build) a system that performs well not just within the confines of a lab, but in the real world.