DeepSeek Elastic Compute (DSec)

swingboy

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

vblanco

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

doc_ick

Will admit that I haven’t read it yet, just saw the crazy number of authors and think this may compete for one of the papers with the most authors.

redat00

So.. serverless ?

Vaslo

That number of authors though

yipinwong

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

throwaway7783

Is this like agent substrate?

flowerlad

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.

jerrygenser

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.

erulabs

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

peter_d_sherman

>"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!

piterrro

12 sandboxes per code is insane, I wonder how many of these sandboxes are idle at a time. Depending on the tasks assigned the resource requirements are different. Compare an agent doing pdf conversion and one responding to a simple question. One is cpu bound the other is mostly network wait. This is an interesting problem from infra perspective since you cannot predict the workload. On a bigger scale you may get away with forecasts. Im waiting for tech that elastically allocates cpu/mem without restarting a container.