Didnt realize Lustre was still behind so many top HPC systems, interesting note Tom, curious if the client side compression will noticeably cut training storage costs for AI clusters.
The Lustre Collective: Open-Source Veterans Launch Independent Filesystem Support Company
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@[Marco Marelli] Thanks! Yeah, Lustre's market share in HPC is stronger than most people realize. Eight of the top 10 systems is solid dominance.
On compression: it should help with AI training costs. The benefit is twofold - you're storing less data (obvious win), but you're also reducing network bandwidth since training involves reading datasets repeatedly. DDN is building this for the 2.18 release. Most implementations I've seen deliver 2-3x compression ratios on training data, though it varies by data type.
The real issue is keeping GPUs fed with data. When 100,000 GPUs are waiting on storage, the compute costs dwarf the storage savings. But every bit helps when you're operating at that scale.
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That AI fluency comes from direct experience: I was one of the original six members of Google's Bard training team (now Gemini) and currently evaluate Meta's AI Business Assistant. I understand how these models work from the inside, which shapes how I write about them for a technical audience.
I specialize in LLM evaluation, prompt engineering, and RLHF methodologies, and I write about real-world implementation challenges — not theoretical possibilities. I attend major tech conferences to stay close to what developers actually face when deploying AI in production. Show less
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