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DeepSeek Elastic Compute (DSec)

201 pointsposted 11 hours ago

61 Comments

flowerlad

6 hours ago

It seems every DeepSeek paper/patent has a huge number of authors, and this one is no exception. They couldn't even fit everyone on the page, there are 31 others not shown. This could be an asset protection strategy (i.e., human assets). Imagine if there were only 3 authors. Those authors may get hired away by competitors. If you list every employee on every paper then competitors don't know who to lure away.

sva_

5 hours ago

Compare to https://arxiv.org/abs/2407.21783

ahurmazda

5 hours ago

Just look for the “corresponding author”

eru

18 minutes ago

The unfortunate intern who had to upload to arxiv?

nextaccountic

2 hours ago

> there are 31 others not shown

just click the link and it will show the others, this seems to be a limitation/UI feature of arxiv. The paper itself contains the full list

CSSer

2 hours ago

I think they just meant that it's so many other people that they don't reasonably fit in the UI

txhwind

4 hours ago

Competitors will try to touch everyone on the list.

anvuong

4 hours ago

Lmao with the conspiracy. Large scale experimental research is always like this, many papers in experimental physics have pages of authors.

alightsoul

3 hours ago

Maybe aquihire like Nvidia with groq?

altmanaltman

3 hours ago

Yeah what possible company can try to lure 100 people... Just for reference, Linkedin has 17,000+ full time employees.

ycui7

5 hours ago

click the link, or read the PDF.

all authors are listed. there is no conspiracy to hide authorship.

arxiv simply want to keep the page short not too long.

phytax

22 minutes ago

Why is this the top comment? Many of the comments, as well as this one, have no relation to content and only mention a triviality

vblanco

8 hours ago

380.000 concurrent sandboxes on 160 Epyc based server nodes. Crazy stuff

dangoodmanUT

7 hours ago

that's only 12 sandboxes per core

aabhay

7 hours ago

Um, how is that not impressive

nijave

4 hours ago

A place I worked back around 2020 was running a Grafana instance per customer that got embedded on the web dashboard. We had 110 pods per GKE (kubernetes on gcp) 4 CPU node because that was a network imposed pod limit at the time. The nodes were usually idle--could have shoved a lot more on if not for the IP limit.

I think around that time Grafana changed their license tho so you couldn't host OSS Grafana as part of your service.

r_lee

6 hours ago

if it's agentic stuff, they likely aren't hammering a core constantly and they will maybe sit idle quite often between model requests, so it makes sense. I do wonder how much memory they allocate to each one though.

it's just very efficient use of shared cores that is required to make these kinds of workloads cost efficient

eru

17 minutes ago

If they sit mostly idle, you can swap out a lot of the memory to SSD, I guess.

m3kw9

3 hours ago

how is it impressive?

erulabs

3 hours ago

Appears to be similar to what Google is building with ax https://github.com/google/ax

yipinwong

6 hours ago

The topic isn't as interesting as how 131 authors communicated to get this out.

stefan_

5 hours ago

I don't understand why half the comments here are about the author list, this is very common practice in e.g. large-scale physics experiments and biology, and every new GPT release from OpenAI equally had papers with tons of authors

hodgehog11

5 hours ago

Agreed, I'm very confused as well. It's like no-one here has been paying attention to research papers.

Or they are just rushing to say anything, and it's much easier to comment on that than the content of the paper.

embedding-shape

6 hours ago

Is it possible they're doing a research lab "socialism style" and everyone gets equal credit for just being a part of the lab, regardless of actual input into the specific papers? If they're innovating in computer, maybe they're not so afraid of innovating in social/academic structures as well?

tonmoy

6 hours ago

This is common practice in Biology labs in the west I think

moritzwarhier

3 hours ago

Maybe there are even reasonable justifications for it, instead of yelling about "socialism".

embedding-shape

3 hours ago

Sorry, didn't mean it like "yelling", I'm quite a fan of socialism and don't see it as any negative. I didn't think anything in my comment was negative.

nextaccountic

2 hours ago

It's negative in the sense it suggest some authors didn't contribute (or contribute little0 to the research, and were perhaps just warm bodies that happened to be present at a certain location

alightsoul

3 hours ago

The west does it too in experimental papers. This is not a socialism thing.

throwaway7783

6 hours ago

Is this like agent substrate?

peter_d_sherman

an hour ago

>"Within one scale unit, the platform spans nearly 160 CPU nodes with 30K cores and ∼250 TB of DRAM. It manages petabytes of layers and images. On a typical day, a single scale unit serves about 3 M sandbox instances, with peak concurrency reaching ∼380K and a creation rate exceeding 5,000 instances per second."

Impressive numbers!

Whoever would have thought (in prior years) that in 2026 AI Agents (not people or corporations, at least not directly) seem to be (or seem to be rapidly becoming) the biggest consumers of cloud computing resources...

Anyway, a very interesting paper and environment!

jerrygenser

5 hours ago

I wonder if they are signalling that if they can do this for training, then they can create an style agent swarm to hack anyone with 380k concurrent agents.

redat00

7 hours ago

So.. serverless ?

redat00

7 hours ago

Still very impressive! Love how it's done!

tipiirai

7 hours ago

Can you give a brief for what this is and why it is impressive?

redat00

6 hours ago

It just describes the platform they built for scheduling workloads, and running those workloads. After a second thought it is not that impressive and probably doesn't deserve any kind of hype. It's the same kind of setup AWS is running for Lambda, as well as anyone else basically running SLURM clusters out there.

Still giving them credit because creating such as scheduler/platform from scratch is quite complex, and I know that they probably struggled a lot to get it right.

calebkaiser

an hour ago

That's not quite right. A recurring trend in ML is figuring out how to get an elastic interface for the the particular quirks of ML workloads (source: I worked on an open source one years ago for inference). Recently, there's been a lot of interest in doing this for agent workloads. Google recently released something called ax that is similar in spirit. The core of it is this: https://github.com/agent-substrate/substrate

At a high level, agent sandboxes have peculiar needs. Agents are really bursty, but also long lived. You need low latency suspend/resume calls. Checkpointing and recovery have some particular considerations. And naive approaches are often really wasteful, but over optimizing without harming durability, isolation, or consistency in performance can get tricky.

This is the new hot infra topic for agent swarms, for the time being. Whether that's impressive or not is up to the reader I guess, but it's a pretty involved project nonetheless.

r_lee

6 hours ago

I'd say it's cool that they're openly writing about it and how they run their workloads. shows a nice window into how these things are actually deployed at scale.

it also shows how much density you can get easily from a single core if you wanted to replicate this

swingboy

9 hours ago

Is there a lab more innovative than DeepSeek? Imagine if they had the same compute resources that Anthropic and OpenAI have.

ProphetOfParado

9 hours ago

Food for thought: Constraints are the source of creativity.

conception

9 hours ago

Yeah if they had the resources of an OpenAI or anthropic they’d be OpenAI or Anthropic. Scrappy underdogs have to be nimble and innovative.

mirekrusin

8 hours ago

They are as “underdog” as Linux is to Windows.

ianm218

6 hours ago

Not really, they are underdogs in the true sense of the word.

rozim

8 hours ago

Possibly relevant: 突破技术壁垒, "break the technical barricade" -> overcome an obstacle through innovation (in this case, sub SOTA GPUs at least).

Native Chinese speakers to confirm....

michaellee8

8 hours ago

your translation is correct, I would say Chinese labs may be able to figure out the current capability of latest frontier models in 3-6 months, but then Anthropic and OpenAI may have already been ASI in that time already. China's main problem is still lack of (good) chips, and that is a hardware issue that is unlikely to be solved for a while. and more effort for efficiency means less effort for actual capability improvements. we have already seen what anthropic can do if they focus on efficiency with opus 5.5

impulser_

9 hours ago

Short term they might have less compute, but long term they will most definitely have more compute. They don't have to worry about energy, they don't have to worry about people blocking them building data centers the only thing stopping them is there no Chinese manufacturer that can produce a chip as good as Nvidia but I would bet that solved in a year or so.

tucnak

6 hours ago

They don't have to worry about people blocking DC construction in the US either. All new AI datacenters are designated "dual-use" so the federal government is already letting local councils know to fuck off.

8note

3 hours ago

they can also put them in better places, vs trying to arbitrage expensive electricity costs and various US corruption thats built more around paying people off than getting things done

ford

2 hours ago

It's hard enough to build them in the US that multiple companies are unironically spending 10s of millions of dollars to try to build them in space

Which cynics could say is marketing hype, but I tend to believe it's extremely difficult to build anything land/energy intensive in the modern United States

impulser_

3 hours ago

Yeah, but that brings up another problem that China doesn't have. Their federal government is always on the same page. The US federal government changes every two years and it doesn't seem like one side is going to be allowing building of AI data centers anymore and in fact might just ban AI in general.

SmartestUnknown

8 hours ago

Just because other companies don't write papers about what they do doesn't mean they aren't innovative...

broodbucket

7 hours ago

I'm actually the most innovative, I've written thousands of papers advancing the state of human knowledge. They're just in my basement and I don't show anyone.