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White Paper: GPU-Initiated, Liquid-Cooled, Ultra-High-Density Storage for Next-Gen AI
This paper introduces a paradigm shift in storage architecture designed to overcome the CPU-centric data path bottlenecks in modern AI workloads. By...
This document is not a specification for OAI/OAM products. It is a set of guidelines on the design, validation, and implementation of liquid cooling solutions for AI Training Systems with 8x OAM products or others alike.
Contents of the document would help a user/designer/supplier of OAI/OAM products understand the basics around those topics/questions related to liquid cooling.
For most engineering topics/questions discussed in this document, we (the OAI Cooling workstream members) are contributing what we believed to be best practices as of today. However, for each product, there would be more than one way to design/validate/use it, not to mention potential technology evolvement or changes of dependencies down the road. Please keep open-minded while reading this document, and do not hesitate to contact us directly for feedback and further discussion.
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This paper introduces a paradigm shift in storage architecture designed to overcome the CPU-centric data path bottlenecks in modern AI workloads. By...
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This paper explores a disaggregated key-value (KV) storage architecture designed to efficiently offload KV cache tensors for generative AI workloads.
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This paper explores an advanced framework designed to automate the extraction of important attributes from unstructured part datasheets. By...