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cedana / throughput · v1.4 · build 2826

GPU job migration
infrastructure.

Cedana checkpoints, migrates, and resumes live GPU jobs across your fleet — raising throughput, reliability, and AI revenue per MW.
Schedule a demoRead the docs
~ / cedana / migrate · livenode-A ─▸ node-B
The Problem → The Fix

AI workloads cannot move once running.
Cedana makes them liquid.

Four ways stranded compute drains budgets — and how Cedana resolves each, live and in place.

~ / cedana / problem ─▸ fix · live● 4 resolved
✕Idle GPUs:: 75% idle└▸Maximize throughput:: 88% util✕Expensive failures:: 65% lost└▸Automated reliability:: 0 lost✕Overprovisioned GPUs:: 50% over└▸Eliminate overprovisioning:: 0% buffer✕Rigid infrastructure:: no adapt└▸Adaptive infrastructure:: real-time
— the problemstatus: degraded
→ with cedanastatus: ok
01ERR.IDLE

Idle GPUs

75% idle
01RESOLVED

Maximize throughput

up to 88% utilization
02FATAL.RESTART

Expensive failures

65% compute lost
02RESOLVED

Automated reliability

0 lost progress
03WASTE.30%

Overprovisioned GPUs

10–50% overprovisioned
03RESOLVED

Eliminate overprovisioning

0% safety buffer
04STUCK.SCHEDULE

Rigid infrastructure

cannot adapt
04RESOLVED

Adaptive infrastructure

real-time
Read how we workSee the lifecycle
Live Proof · Console
Cold-Start Race

Same model. Same hardware.
21.7× faster to first token.

GLM-5.2-FP8 · 753B MoE · Multimodal · vLLM v0.19.0 · TP=8 · 8× B200 · 734 GiB ckpt · elapsed 00:00.00s
NATIVE · vLLM v0.19.0 · TP=8
● COLD START
00:00.00
$ vllm serve zai-org/GLM-5.2-FP8 --tp=8
INFO 00:00:03   spawning 8 workers · EP=8
INFO 00:00:40   loading shards 12/94 …
INFO 00:05:00   loading shards 40/94 …
INFO 00:12:00   loading shards 78/94 …
INFO 00:16:20   loading shards 94/94 …
INFO 00:18:40   building cuda graph (×8)
INFO 00:20:30   warming kv cache · vision tower
INFO 00:21:30   jit compile attention
CEDANA · RESTORE
▲ WARM RESUME
00:00.00
$ cedana resume glm-5.2-fp8 --from=snap.az-1
[+] fetch snapshot     :: ok    (734 GiB · memlock)
[+] verify hash        :: ok    (sha256: c4e1…9a)
[+] restore cuda ctx   :: ok    (8× driver attached)
[+] repopulate gpu mem :: ok    (weights + KV)
[+] thaw connections   :: ok    (sockets)
[+] register endpoint  :: ok    (port 8000)
READY 00:01:01   first token
NATIVE
0.0s
CEDANA
0.0s
delta · −1261s savedspeedup · 21.7×verdict · cedana wins
Advanced · Status: SCALING

Built for the hardest workloads.

01 · ADVANCED WORKLOADS

Distributed by default.
Works transparently with MPI & NCCL.

02 · SCALE

From a single node to an AI factory.

The Platform

unlock() your scheduler.

01

Work with what you have

No rip-and-replace. No code changes. No disruption to your teams.

02

Kubernetes & SLURM

Built for AI and HPC. Native support for SLURM and Kubernetes.

03

First migration in <30 min

K8s helm chart or SLURM plug-in. No changes to your config.

~ / cedana / deploy● ready

Command your
compute.

Your compute, liquid — checkpoint, migrate, and resume live GPU jobs across the fleet.

Schedule a demoRead the docs
deployK8s helm chart · SLURM plug-in
first migration<30 min
code changes0
workloadstraining · inference · HPC
01
AWS
02
Google Cloud
03
NVIDIA
04
K8s
05
SLURM
06
Nvidia Dynamo