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ozereray1 4 hours ago [-]
RISC V making its way into proper server platforms is a huge milestone. The open architecture could eventually disrupt the current vendor lock in we see in cloud data centers.
speed_spread 1 hours ago [-]
I don't doubt RISC-V can be used to make powerful cores but adoption as a general purpose CPU (rather than MCU) will need more than good numbers.
There's still a missing piece in the RISC-V ecosystem: a coordination body of platform-level standards. Debian took a stand with RVA23 support but then there's a ton of little things that are taken for granted on the PC platform such as UEFI and ACPI (as horrible as they may be).
surajrmal 30 minutes ago [-]
risc-v is basically borrowing the ARM SystemReady stuff. This includes the expectations for ACPI and UEFI on servers. The RISE organization has been trying to drive these standards iiuc.
fragmede 3 hours ago [-]
Which axis of vendor lock in are you seeing possibly being disrupted by this? x86 is rather dominant, though ARM is making a play. RISC V just means AWS offers a different ISA on compute, you'd still be vendor lock-in'd to AWS/whomever. Or I'm totally not getting it.
matt-p 1 hours ago [-]
Obviously not OP, but:
Lock-in to x86 or ARM is painful from an operator like AWSs perspective. With x86 you end up with two vendors to play off against each other, which isn't great. ARM gives you the ability to design your own silicon, but you're still beholden to a single licensor -- arguably worse. On top of that, some customers mandate a specific ISA or even a specific vendor, so none of it is truly fungible outside vertically integrated workloads like S3.
The ideal scenario for a hyperscaler is an open architecture at the core with 10+ competing implementations -- including potentially their own.
mosura 48 minutes ago [-]
> The ideal scenario for a hyperscaler is an open architecture at the core with 10+ competing implementations -- including potentially their own.
This is what Arm actually is. Arm primarily functions as a talking shop for random insights to get back from integrators into the ISA and architecture, then cleared and released for everyone to use. The reason there are so few novel implementations of it is it just isn’t worth the trouble unless you are pushing mobile levels of units.
surajrmal 37 minutes ago [-]
Considering how consolidated the hyperscalar market is and their natural inclination to reduce hardware SKUs, I'm not entirely sure they would make it viable for multiple vendors to produce chips they could actually use. There is no reason to believe it'll work out differently from the ARM server market.
yjftsjthsd-h 7 hours ago [-]
> Support for double-wide GPUs (Up to 450W)
I wonder how the driver situation is. From Jeff Geerling's work on running "big" GPUs on Raspberry Pis, my impression is that often less-common platforms should work but are littered with papercuts in practice.
jogu 7 hours ago [-]
AMD GPUs have worked on RISC-V for a couple years at this point. I have a Milk-V Titan that's paired with an AMD GPU running well: https://milkv.io/titan
sylware 4 hours ago [-]
Maybe a Zen microarchitecture with a RISC-V/RVA front-end?
While thinking about it, if NVIDIA or SAMSUNG go performant RISC-V CPU micro-architecture, will "probably" change the world.
dlcarrier 7 hours ago [-]
…and when it comes to the most common use of big-iron GPUs right now, neural network engines, they're all so poorly put together that a papercut is often fatal. If every dependency isn't the exact needed version, the whole thing will collapse, and using all but the most common hardware is sure to be unsupported in some deprecated library version that is absolutely required to get everything running.
I had thought Xilinx ISE and Altera Quartus had the market cornered on the most difficult environments to get running, but then LLMs and stable diffusion came along.
qrios 4 hours ago [-]
> I had thought Xilinx ISE and Altera Quartus had the market cornered on the most difficult environments to get running, …
These tools were the reason why I gave up on FPGAs years ago and chose to spend my time on GPUs instead. And to this day, I still don't understand why they worked so differently from what I had expected in so many ways.
mosura 2 hours ago [-]
You haven’t lived until you have done a model training run where different stages require mutually incompatible nvidia driver revisions and everything on top.
sylware 4 hours ago [-]
That's why _LEAN_ open source is really required, and that includes the SDK.
cultofmetatron 5 hours ago [-]
> Support for double-wide GPUs (Up to 450W)
oh a double wide surprise for the AI industry? just what we needed.
256gb ddr5, so this is going to cost north of 100k? Damn.
arjie 3 hours ago [-]
No way, it's only like 4x64 GB of ECC DDR5 5600 RDIMMs. Who's paying $100k for that? I'll gladly sell them this at a 10% discount.
Havoc 6 hours ago [-]
Can’t see myself buying my this but glad riscv is making progress.
sylware 4 hours ago [-]
Missing the silicon process.
stonogo 26 minutes ago [-]
It's TSMC N6. What does that information benefit you? We're still talking about a boutique chip that's not going to outperform anything from the past decade's worth of amd64 products.
There's still a missing piece in the RISC-V ecosystem: a coordination body of platform-level standards. Debian took a stand with RVA23 support but then there's a ton of little things that are taken for granted on the PC platform such as UEFI and ACPI (as horrible as they may be).
Lock-in to x86 or ARM is painful from an operator like AWSs perspective. With x86 you end up with two vendors to play off against each other, which isn't great. ARM gives you the ability to design your own silicon, but you're still beholden to a single licensor -- arguably worse. On top of that, some customers mandate a specific ISA or even a specific vendor, so none of it is truly fungible outside vertically integrated workloads like S3.
The ideal scenario for a hyperscaler is an open architecture at the core with 10+ competing implementations -- including potentially their own.
This is what Arm actually is. Arm primarily functions as a talking shop for random insights to get back from integrators into the ISA and architecture, then cleared and released for everyone to use. The reason there are so few novel implementations of it is it just isn’t worth the trouble unless you are pushing mobile levels of units.
I wonder how the driver situation is. From Jeff Geerling's work on running "big" GPUs on Raspberry Pis, my impression is that often less-common platforms should work but are littered with papercuts in practice.
While thinking about it, if NVIDIA or SAMSUNG go performant RISC-V CPU micro-architecture, will "probably" change the world.
I had thought Xilinx ISE and Altera Quartus had the market cornered on the most difficult environments to get running, but then LLMs and stable diffusion came along.
These tools were the reason why I gave up on FPGAs years ago and chose to spend my time on GPUs instead. And to this day, I still don't understand why they worked so differently from what I had expected in so many ways.
oh a double wide surprise for the AI industry? just what we needed.
is it opensource or megs of blob?