Sine Nomine Associates - OpenAFS AI Use Case 6 -Shared LLM Inference Artifacts

EntSun -- Use case: Multiple inference servers need access to the same set of large model weights.

OpenAFS advantage:
Efficient read-only caching for model weights across inference nodes.

Avoids redundant downloads from cloud or object storage.

Enables faster startup and consistent model deployment across nodes.

Integration Notes
OpenAFS can integrate with modern AI stacks using:
FUSE mounts for transparent access in containerized environments (e.g., Kubernetes).
Cache tuning for large file access patterns typical in LLM workloads.
Bridging with S3 gateways or caching proxies for hybrid setups.

Sine Nomine Associates has a long history going back over 25 years to the beginning of OpenAFS. Our team of experts helps many in several industries with repeated support services contracts.

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Our in-house team of five includes two of the maintainers for the OpenAFS open-source code. Our unique capabilities have kept OpenAFS up to date with modern tools like ansible. Our mainframe team supports several opensource projects, Linux on z/VM, docker, Kubernetes, zookeeper and many others.

Margarete Ziemer, CEO, emphasizes: "We are proud to say we continue to support the open-source community with a sharp focus on the mainframe, advanced technology workspace concepts and OpenAFS areas. We sincerely thank all our past and current customers and our associates. We are always ready to tackle your problems with custom solutions, particularly in the open-source space."

For more information on Sine Nomine Associates and their products, please visit our website.
https://sinenomine.net (https://sinenomine.net/index.php/openafs/)