Ask Lemmy
A Fediverse community for open-ended, thought provoking questions
Please don't post about US Politics.
Rules: (interactive)
1) Be nice and; have fun
Doxxing, trolling, sealioning, racism, and toxicity are not welcomed in AskLemmy. Remember what your mother said: if you can't say something nice, don't say anything at all. In addition, the site-wide Lemmy.world terms of service also apply here. Please familiarize yourself with them
2) All posts must end with a '?'
This is sort of like Jeopardy. Please phrase all post titles in the form of a proper question ending with ?
3) No spam
Please do not flood the community with nonsense. Actual suspected spammers will be banned on site. No astroturfing.
4) NSFW is okay, within reason
Just remember to tag posts with either a content warning or a [NSFW] tag. Overtly sexual posts are not allowed, please direct them to either [email protected] or [email protected].
NSFW comments should be restricted to posts tagged [NSFW].
5) This is not a support community.
It is not a place for 'how do I?', type questions.
If you have any questions regarding the site itself or would like to report a community, please direct them to Lemmy.world Support or email [email protected]. For other questions check our partnered communities list, or use the search function.
Reminder: The terms of service apply here too.
Partnered Communities:
Logo design credit goes to: tubbadu
view the rest of the comments
Man, no kidding. We've got SoCs, we've got processors running on the FPGA fabric, we've got communications to Ethernet, PCIe, any AXI you like really. They can talk to RAM, storage, other processors, output graphics, kiss me on the forehead, and tuck me in at night. (I think.)
A coworker was telling me about the big shots in New York trading companies that are starting to implement FPGA architectures into their high-frequency trading algorithms, as the blazing high speed and great parallelization helps them squeeze out a couple extra microseconds in their algorithms. I think that's a good sign of people wising up to this potential here.
I don't know of any ML training on FPGAs, but I have no doubt that it can be / it is being done.
Edit: I just remembered the other day, I was shown a module that could take in a grey scale image, do edge dection, and output the edges as a new image file. Which isn't that hard, it's convolution on a sliding window, but what baffled me is that it was done in fewer cycles than could be compiled through C code, and the pipeline wasn't even that deep. It's crazy!
your eyes do this, the cells in your eyes do a variety of edge detection and orientation detection before passing on this preprocessed image to the brain where the brain processes it further
Ya, it's fun stuff. We're using ML for particle identification and tracking in high-energy physics. It's magnitudes faster than anything a CPU/GPU can do..