3 ms·

> especially once you're in embedded is this a real problem? exactly which embedded platform has a device that ROCm supports?

mikepurvis 3y ago
Robotic perception is the one relevant to me. You want to do object recognition on an industrial x86 or Jetson-type machine, without having to use Ubuntu or whatever the one "blessed" underlay system is (either natively or implicitly because you pulled a container based on it).
- mathisfun123 3y ago
  >industrial x86 or Jetson-type machine that's not embedded dev. if you 1. use underpowered devices to perform sophisticated tasks 2. using code/tools that operate at extremely high levels of "abstraction" don't be surprised when all the inherent complexity is tamed using just more layers of "abstraction". if that becomes a problem for your cost/power/space budget then reconsider choice 1 or choice 2.
  - mikepurvis 3y ago
    Not sure this is worth an argument over semantics, but modern "embedded" development is a lot bigger than just microcontrollers and wearables. IMO as soon as you're deploying a computer into any kind of "appliance", or you're offline for periods of time, or you're running on batteries or your primary network connection is wireless... then yeah, you're starting to hit the requirements associated with embedded and need to seek established solutions for them, including using distros which account for those requirements.
    - mathisfun123 3y ago
      > IMO as soon as you're deploying a computer into any kind of "appliance", or you're offline for periods of time, or you're running on batteries or your primary network connection is wireless yes and in those instances you do not reach for pytorch/tensorflow on top of ubuntu on top of x86 with a discrete gpu and 32gb of ram. instead you reach for C and micro or some arm soc that supports baremetal or at most rtos. that's embedded dev. so i'll repeat myself: if you want to run extremely high-level code then don't be "surprised pikachu" when your underpowered platform, that you chose due to concrete, tight budgets doesn't work out.
      - nightski 3y ago
        Clearly you've never used a Nvidia Jetson and have no idea what it is. You don't need a discrete GPU, it has a quite sophisticated GPU in the SoC. It's Nvidia's embedded platform for ML/AI.
      - Const-me 3y ago
        The hardware can be fast, actually. Here’s an example of relatively modern industrial x86: https://www.onlogic.com/ml100g-41/ https://www.onlogic.com/ml100g-41/ That thing is probably faster than half of currently sold laptops. However, containers or Ubuntu Linux don’t perform great in that environment. Ubuntu is for desktops, containers are for cloud data centers. An offline stand-alone device is different. BTW, end users don’t typically aware that thing is a computer at all. Personally, I usually pick Alpine or Debian Linux for similar use cases, bare metal i.e. without any containers.
        ngcc_hk 3y ago
        That is the moat they tried to cross. Imagine you have a PyTorch app and run on iOS, arm based, amd based and intel … cloud, or embedded. just imagine. You scale and embed as your business case, not as any one firm current strategy is. Or at least you have some case as heaven never come. Or come just we do not aware now like internet. Can you need to use ibm to rub sna to provide a token ring based network. In 1980 … Imagine and let us or they competite …
        cannonpalms 3y ago
        > Ubuntu is for desktops Tell that to their (much larger, more profitable, and better-funded) server org. This is far from true.
        iopq 3y ago
        It also works much better as a server. Snaps work really well for things like certbot On Desktop you have to worry about things like... UIs, sound, Wine, etc.
      - rcxdude 3y ago
    - serf 3y ago
      fwiw CompTIA classifies an embedded engineer/developer as " those who develop an optimized code for specific hardware platforms."

mikepurvis 3y ago

Robotic perception is the one relevant to me. You want to do object recognition on an industrial x86 or Jetson-type machine, without having to use Ubuntu or whatever the one "blessed" underlay system is (either natively or implicitly because you pulled a container based on it).

mathisfun123 3y ago
>industrial x86 or Jetson-type machine that's not embedded dev. if you 1. use underpowered devices to perform sophisticated tasks 2. using code/tools that operate at extremely high levels of "abstraction" don't be surprised when all the inherent complexity is tamed using just more layers of "abstraction". if that becomes a problem for your cost/power/space budget then reconsider choice 1 or choice 2.
- mikepurvis 3y ago
  Not sure this is worth an argument over semantics, but modern "embedded" development is a lot bigger than just microcontrollers and wearables. IMO as soon as you're deploying a computer into any kind of "appliance", or you're offline for periods of time, or you're running on batteries or your primary network connection is wireless... then yeah, you're starting to hit the requirements associated with embedded and need to seek established solutions for them, including using distros which account for those requirements.
  - mathisfun123 3y ago
    > IMO as soon as you're deploying a computer into any kind of "appliance", or you're offline for periods of time, or you're running on batteries or your primary network connection is wireless yes and in those instances you do not reach for pytorch/tensorflow on top of ubuntu on top of x86 with a discrete gpu and 32gb of ram. instead you reach for C and micro or some arm soc that supports baremetal or at most rtos. that's embedded dev. so i'll repeat myself: if you want to run extremely high-level code then don't be "surprised pikachu" when your underpowered platform, that you chose due to concrete, tight budgets doesn't work out.
    - nightski 3y ago
      Clearly you've never used a Nvidia Jetson and have no idea what it is. You don't need a discrete GPU, it has a quite sophisticated GPU in the SoC. It's Nvidia's embedded platform for ML/AI.
    - Const-me 3y ago
      The hardware can be fast, actually. Here’s an example of relatively modern industrial x86: https://www.onlogic.com/ml100g-41/ https://www.onlogic.com/ml100g-41/ That thing is probably faster than half of currently sold laptops. However, containers or Ubuntu Linux don’t perform great in that environment. Ubuntu is for desktops, containers are for cloud data centers. An offline stand-alone device is different. BTW, end users don’t typically aware that thing is a computer at all. Personally, I usually pick Alpine or Debian Linux for similar use cases, bare metal i.e. without any containers.
      - ngcc_hk 3y ago
        That is the moat they tried to cross. Imagine you have a PyTorch app and run on iOS, arm based, amd based and intel … cloud, or embedded. just imagine. You scale and embed as your business case, not as any one firm current strategy is. Or at least you have some case as heaven never come. Or come just we do not aware now like internet. Can you need to use ibm to rub sna to provide a token ring based network. In 1980 … Imagine and let us or they competite …
      - cannonpalms 3y ago
        > Ubuntu is for desktops Tell that to their (much larger, more profitable, and better-funded) server org. This is far from true.
        iopq 3y ago
        It also works much better as a server. Snaps work really well for things like certbot On Desktop you have to worry about things like... UIs, sound, Wine, etc.
    - rcxdude 3y ago
  - serf 3y ago
    fwiw CompTIA classifies an embedded engineer/developer as " those who develop an optimized code for specific hardware platforms."