cedana.com valid
Cedana
Cedana provides GPU and CPU workload save, migrate, and resume infrastructure for AI, HPC, inference, training, spot capacity, and scientific computing workloads.
- Authority
- 46 reach 0 · trust 10 · quality 21 · freshness 15
- Tier
- listed
- llms.txt
- https://cedana.com/llms.txt
- Sections
- 4
- Links
- 120
- Size
- 29301 bytes
- Registered
- 2011-07-07
- Country
- United States Hosting inference
- Hosting country
- United States Hosting inference
- Country evidence
- No published address evidence collected yet
- For agents
- Documentation: developer or product docs worth reading, nothing to call
- First seen
- 2026-10-23T11:18:01.480Z
- Last checked
- 2026-10-23T11:18:03.431Z
- Badge
Their llms.txt
The beginning of the file, from our validated copy saved 2026-10-23T11:18:01.495Z. Cached copy · Source on cedana.com
# Cedana
> Cedana provides GPU and CPU workload save, migrate, and resume infrastructure for AI, HPC, inference, training, spot capacity, and scientific computing workloads.
Use this file as a curated map of the key Cedana pages and all published blog posts.
## Canonical Pages
- [Cedana | GPU Job Migration Infrastructure](https://cedana.com/)
- [About Cedana | Compute Infrastructure for AI Factories](https://cedana.com/about/)
- [Schedule a Cedana Demo](https://cedana.com/demo/)
- [Cedana Blog | Engineering Notes and Field Reports](https://cedana.com/blog/)
- [How Cedana Works | Save, Migrate, Resume Workloads](https://cedana.com/product/how-it-works/)
- [Cedana Performance | Improve Utilization and Reduce Cost](https://cedana.com/product/performance/)
- [Cedana Orchestration | Real-Time Compute Orchestration](https://cedana.com/product/orchestration/)
- [Cedana Reliability | Unbreakable AI and HPC Workloads](https://cedana.com/product/reliability/)
- [Automatic Spot Workloads](https://cedana.com/use-cases/auto-spot/)
- [Cedana for HPC and Computational Biology](https://cedana.com/use-cases/comp-bio/)
- [Elastic Inference on Your Infrastructure](https://cedana.com/use-cases/inference/)
- [Distributed Training Reliability](https://cedana.com/use-cases/training/)
- [Cedana for Pharma and Biotech | GPU Infrastructure for R&D](https://cedana.com/solutions/pharma-biotech/)
- [Cedana for Research Computing | GPU Cluster Utilization](https://cedana.com/solutions/research-computing/)
- [Cedana for AI Inference Providers | Cold Starts in Seconds](https://cedana.com/solutions/inference-providers/)
- [Cedana for Neoclouds and GPU Clouds | More Revenue per Megawatt](https://cedana.com/solutions/neoclouds/)
- [Cedana for Digital-Native and Consumer Tech | GPU Inference at Scale](https://cedana.com/solutions/digital-native/)
## Blog Posts
- [Serve a Portfolio of Coding Models on a Single Node with NVIDIA Dynamo, NeMo Switchyard and Cedana](https://cedana.com/blog/coding-model-portfolio-single-node/): Host a portfolio of frontier coding models on one 8x B200 node. NVIDIA Dynamo serves, NeMo Switchyard routes and escalates, and Cedana switches models in about a minute with sessions intact.
- [How to choose a GPU for LLM inference](https://cedana.com/blog/choose-gpu-llm-inference/): Build an inference GPU shortlist using your traffic, memory needs, precision, latency, interconnect and rack cost, then measure startup and recovery on your path.
- [What roofline analysis cannot see: the costs outside the steady state](https://cedana.com/blog/roofline-analysis-limitations/): Add startup, recovery and movement time to your inference measurements. Understand what steady-state roofline analysis explains and which fleet costs sit outside it.
- [What Cedana saves, and what it does not](https://cedana.com/blog/what-cedana-saves/): See which GPU, process, file, network and scheduler state Cedana saves, what remains outside the checkpoint, and what a compatible restore r
…Machine-readable: GET /v1/resolve?q=cedana.com · GET /v1/domain/cedana.com · this page as Accept: application/json or text/markdown · MCP lookup_domain
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