5 ms·

That looked interesting as a self-hostable project until it got to the requirement for a $3200 AMD board. Maybe the price will come down one day...

15155 2y ago
~400kLUT is very obtainable these days - if you don't need the ARM cores: https://www.lcsc.com/product-detail/Programmable-Logic-Device-CPLDs-FPGAs_AMD-XILINX-XC7K410T-2FFG900I_C2937666.html https://www.lcsc.com/product-detail/Programmable-Logic-Devic... (420T/480T are priced similarly new.)
DoingIsLearning 2y ago
The ultrascale is definitely pricy for non-industry applications. The FPGA design is probably larger because of the 4x camera pipeline. Perhaps with a single camera you could port this to fit on a Zynq 7000 footprint with something like a Pynq Z1 or Numato Styx, which are in the $250 hobbies price point for example.
- 15155 2y ago
  No chance does the Zynq 701x series perform capably for this task: it's weak Artix fabric and there's only ~50kLUT on the common parts. Even fully pipelined designs, especially those that interface with the hard AXI bus, will struggle to clock above 50MHz. The Zynq Z7030+ chip would probably be able to get the job done but aren't as common - https://www.lcsc.com/product-detail/Programmable-Logic-Device-CPLDs-FPGAs_AMD-XILINX-XC7Z030-2FFG676I_C966962.html https://www.lcsc.com/product-detail/Programmable-Logic-Devic.... The Kintex 410T-480T are available new <$160 from reputable vendors, used <$50 from less-reputable vendors - they do have the performance (and overall IO) for this task.
dailykoder 2y ago
At the moment I am wondering if I could build an accelerator for george hotz' tinygrad[1] with cheap FPGAs (i do have an arty a7 35K, this might be too small, i guess?). According to the readme it shall be "easy" to add new accelerator hardware. Sadly my knowledge is still a bit limited around all the python-machinelearning-ecosystem, but if I understand it correctly you "just" need an openCL kernel and need to be able to shove the data back and forth somehow. Didn't have enough time to dive into it yet and still working on some other project, but this still tickles the back of my head and would be cool even if I could only run mnist on it. - [1] https://github.com/tinygrad/tinygrad/ https://github.com/tinygrad/tinygrad/
- gh02t 2y ago
  > but if I understand it correctly you "just" need an openCL kernel and need to be able to shove the data back and forth somehow. To use it with an FPGA accelerator you also have to build all the "hardware" to run said openCL kernel efficiently, manage data transfer, talk to the host, etc for the FPGA. This is very foreign if you're only used to doing software design and still very nontrivial even if you've done FPGA work, though I think there are some open hardware projects around doing this.
  - dailykoder 2y ago
    Yeah, i think the, especially efficient, data transfer would be my biggest enemy. I did quite a lot FPGA stuff in recent years, mainly CPU design stuff, a little pipelining and some hardware-software-codesign. So I should just see it as a toy project, start with said mnist to get atleast something running, don't matter if it's efficient and then work my way up. For example I haven't done anything PCIe related yet, but I guess there is enough IP available
    - 15155 2y ago
      Transceivers are the only option for high-speed connectivity - this means PCIE or 100GbE.
sorenjan 2y ago
Depending on what you're trying to do you might not need it. A popular option for object detection people use with their home hosted video surveillance (using Frigate and Home Assistant) is the Coral TPU and Raspberry Pi or some decommissioned thin client.
- muxamilian 2y ago
  Google Coral seems abandoned by Google. Not official but last news on their page from May 2022
  - geerlingguy 2y ago
    I've heard from the folks at Pineboard[1] there's been some new activity, as this year manufacturing ramped back up... it's still decent hardware but is getting long in the tooth. Regarding the Hailo featured in the article, a few of us have been messing with it on a Raspberry Pi 5[2], and it offers more performance in a similar power envelope. The major downside is availability. I can buy the Coral on many electronics supplier sites, but Hailo seems to be selling through 'Product inquiry' right now, which is not easy to navigate as an individual! [1] https://pineboards.io https://pineboards.io [2] https://pipci.jeffgeerling.com/cards_m2/hailo-8-ai-module.html https://pipci.jeffgeerling.com/cards_m2/hailo-8-ai-module.ht...
    - algo_trader 2y ago
      Any good write up on Hailo and similar ? BTW, is it possible to have 10 of these connected to a single board/cpu ?
      - muxamilian 2y ago
        Maybe not 10 but in principle it’s possible: https://www.lannerinc.com/products/edge-ai-appliance/deep-learning-accelerators/falcon-h8 https://www.lannerinc.com/products/edge-ai-appliance/deep-le...
      - geerlingguy 2y ago

15155 2y ago

~400kLUT is very obtainable these days - if you don't need the ARM cores: https://www.lcsc.com/product-detail/Programmable-Logic-Device-CPLDs-FPGAs_AMD-XILINX-XC7K410T-2FFG900I_C2937666.html https://www.lcsc.com/product-detail/Programmable-Logic-Devic... (420T/480T are priced similarly new.)

DoingIsLearning 2y ago

The ultrascale is definitely pricy for non-industry applications. The FPGA design is probably larger because of the 4x camera pipeline. Perhaps with a single camera you could port this to fit on a Zynq 7000 footprint with something like a Pynq Z1 or Numato Styx, which are in the $250 hobbies price point for example.

15155 2y ago
No chance does the Zynq 701x series perform capably for this task: it's weak Artix fabric and there's only ~50kLUT on the common parts. Even fully pipelined designs, especially those that interface with the hard AXI bus, will struggle to clock above 50MHz. The Zynq Z7030+ chip would probably be able to get the job done but aren't as common - https://www.lcsc.com/product-detail/Programmable-Logic-Device-CPLDs-FPGAs_AMD-XILINX-XC7Z030-2FFG676I_C966962.html https://www.lcsc.com/product-detail/Programmable-Logic-Devic.... The Kintex 410T-480T are available new <$160 from reputable vendors, used <$50 from less-reputable vendors - they do have the performance (and overall IO) for this task.

dailykoder 2y ago

At the moment I am wondering if I could build an accelerator for george hotz' tinygrad[1] with cheap FPGAs (i do have an arty a7 35K, this might be too small, i guess?). According to the readme it shall be "easy" to add new accelerator hardware. Sadly my knowledge is still a bit limited around all the python-machinelearning-ecosystem, but if I understand it correctly you "just" need an openCL kernel and need to be able to shove the data back and forth somehow. Didn't have enough time to dive into it yet and still working on some other project, but this still tickles the back of my head and would be cool even if I could only run mnist on it. - [1] https://github.com/tinygrad/tinygrad/ https://github.com/tinygrad/tinygrad/

gh02t 2y ago
> but if I understand it correctly you "just" need an openCL kernel and need to be able to shove the data back and forth somehow. To use it with an FPGA accelerator you also have to build all the "hardware" to run said openCL kernel efficiently, manage data transfer, talk to the host, etc for the FPGA. This is very foreign if you're only used to doing software design and still very nontrivial even if you've done FPGA work, though I think there are some open hardware projects around doing this.
- dailykoder 2y ago
  Yeah, i think the, especially efficient, data transfer would be my biggest enemy. I did quite a lot FPGA stuff in recent years, mainly CPU design stuff, a little pipelining and some hardware-software-codesign. So I should just see it as a toy project, start with said mnist to get atleast something running, don't matter if it's efficient and then work my way up. For example I haven't done anything PCIe related yet, but I guess there is enough IP available
  - 15155 2y ago
    Transceivers are the only option for high-speed connectivity - this means PCIE or 100GbE.

sorenjan 2y ago

Depending on what you're trying to do you might not need it. A popular option for object detection people use with their home hosted video surveillance (using Frigate and Home Assistant) is the Coral TPU and Raspberry Pi or some decommissioned thin client.

muxamilian 2y ago
Google Coral seems abandoned by Google. Not official but last news on their page from May 2022
- geerlingguy 2y ago
  I've heard from the folks at Pineboard[1] there's been some new activity, as this year manufacturing ramped back up... it's still decent hardware but is getting long in the tooth. Regarding the Hailo featured in the article, a few of us have been messing with it on a Raspberry Pi 5[2], and it offers more performance in a similar power envelope. The major downside is availability. I can buy the Coral on many electronics supplier sites, but Hailo seems to be selling through 'Product inquiry' right now, which is not easy to navigate as an individual! [1] https://pineboards.io https://pineboards.io [2] https://pipci.jeffgeerling.com/cards_m2/hailo-8-ai-module.html https://pipci.jeffgeerling.com/cards_m2/hailo-8-ai-module.ht...
  - algo_trader 2y ago
    Any good write up on Hailo and similar ? BTW, is it possible to have 10 of these connected to a single board/cpu ?
    - muxamilian 2y ago
      Maybe not 10 but in principle it’s possible: https://www.lannerinc.com/products/edge-ai-appliance/deep-learning-accelerators/falcon-h8 https://www.lannerinc.com/products/edge-ai-appliance/deep-le...
    - geerlingguy 2y ago