[HN Gopher] What Is Specialized Hardware and Why Open Source Wil...
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What Is Specialized Hardware and Why Open Source Will Drive
Adoption
Author : mrmrcoleman
Score : 68 points
Date : 2021-02-26 10:29 UTC (12 hours ago)
(HTM) web link (metal.equinix.com)
(TXT) w3m dump (metal.equinix.com)
| exikyut wrote:
| I guess the most relevant question within an open source context
| is, "okay, but when/how do we get to play with this fancy new
| hardware?"
|
| OpenPOWER remains a massive niche - as in, it's big, but it's
| still a niche - because nobody (in the sense of "just anybody",
| ie the long tail) can really get their hands on it. It's
| nontrivially difficult to maintain access to IBM POWER8 kit, and
| the Talos is also certainly way beyond what I could personally
| afford from a "directionless tinkering/learning" standpoint.
|
| If I understand this article correctly, cloud-native means
| there's not likely to be a Talos equivalent for sale, and it's
| all remote access only.
|
| Also, OpenPOWER is, like, an entire CPU, with a design is
| extremely old and can be expected to stay around for a long time,
| and even with that sort of centralizable focus opportunity it's
| still a niche.
|
| I get the impression this is suggesting the creation of custom
| components with somewhat shorter design lifecycles - years,
| certainly, but not multiples of decades, and maybe only months
| for individual hardware revisions.
|
| If this really wants to attract developers from outside of the
| immediate focus of the relevant industries... how are the
| discoverability and accessibility equations going to be solved?
|
| Of course, the more potential cooks you attract to the kitchen
| the more overheads you have to deal with, but I wonder if is a
| necessary element to maintain interest and familiarity with what
| would apparently prefer to be a fast-changing environment.
| mrmrcoleman wrote:
| "how are the discoverability and accessibility equations going
| to be solved?" - this is the whole challenge.
|
| I referred to the WorksonARM project in the blog:
| https://www.worksonarm.com/
|
| WorksOnARM solved this problem for ARM by making machines
| available through Equinix Metal's API for development and
| testing.
|
| Hardware manufacturers can ship boxes to developers, give them
| access through an API like Equinix Metal's, or some other
| approach, but one way or another developers are going to need
| access.
| imtringued wrote:
| This article didn't mention PIM (processing in memory) which is a
| way of keeping the established general purpose CPU model and
| accelerating it by simply adding processors directly into RAM.
| The compute power scales with the size of your dataset. You also
| benefit from greater memory bandwidth and lower power
| consumption.
|
| Here is an existing implementation: https://www.upmem.com/
| mrmrcoleman wrote:
| Hey, thanks for the link! This post will be followed up with a
| series of articles that will go into more detail about the
| various technologies. I'll be sure to include PIM in my
| research.
| jleahy wrote:
| Presumably your computing power scales with the number of 'data
| processors' rather than the size of your dataset per se. In the
| same way that you might say "if you use GPUs your computing
| power scales with the size of your dataset" (as you buy more
| GPUs to get more memory, thus get more compute).
|
| But how does this differ to a CPU or GPU? Both are just DRAM
| with something bolted onto the side, and both have a limited
| bandwidth between the DRAM and the processors. The difference
| with putting the processors on the DIMMs is that you now have
| an extremely restrictive thermal envelope to work within (and
| if you put it on the same die, which I hope you're not, then a
| CMOS technology that's supremely ill suited to computation).
| sitkack wrote:
| https://en.wikipedia.org/wiki/Computational_RAM and
| http://iram.cs.berkeley.edu/
|
| I ran into one of these companies, in 2015? at a big data
| conference. The founders claimed to have not known about iram,
| ;) It feels like PIM comes up every couple years, but ram is
| expensive already, and these chips are going to be some
| multiple more expensive. There is some inflection point ,memory
| bandwidth, power, something that will enable PIM to finally get
| traction.
|
| The immediate problem was tooling, os support, supply, scale,
| etc. I think it would make a lot of sense to get this stuff
| installed sitewide _after_ your code has been tuned for
| support. So it needs a good simulator or it needs an interposer
| so one can code to the ABI of the hardware.
|
| I could see a big super computer initiative being used a test
| bed, probably one designed for genomics. I think we
| overestimate how effective and easy to use PIM (processing in
| ram) could be. Where it will really start to shine is when the
| processor can retire instructions into the PIM, pre-materialize
| data streams from the PIM, do a scheduled reduction and then
| push compute bundles back to memory. The computational ram
| needs to be integrated with cpu, it can't _just_ be an
| accelerator.
|
| Computational disks might be way way easier to implement. We
| will know how that is going as soon as Western Digital tells
| us.
|
| https://github.com/chipsalliance/Cores-SweRV
| mrmrcoleman wrote:
| Thanks for the references sitkack
| mwcampbell wrote:
| > Kubernetes and its family of cloud native projects
| revolutionized computing in 4 short years.
|
| This strikes me as wild hyperbole. It's a new management layer
| for server-side computing -- nothing compared to the changes
| brought by microprocessors, or even by minicomputers like the DEC
| PDP line.
| jgalt212 wrote:
| Even more so if you can cram more and more processor cores into
| a chip, or more and more sockets into a board. It's easy to
| envision and multi-socket ARM server making more than a few
| micro service based architectures unnecessary.
| WaitWaitWha wrote:
| I am unclear of the article's target.
|
| Your article implies we are reading about HW manufacturers that
| have prioritization & work load issues, but then you mention
| Apple, AWS, et al. These HW designs are all directed work to the
| HW manufacturer. There is no concerns of prioritization, or work
| load. They get paid handsomely for making the right choices.
| sitkack wrote:
| It is a not so hidden message to industry about what Equinix is
| doing in the cloud server space.
| [deleted]
| [deleted]
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