EPISODE · Apr 23, 2026 · 4 MIN
Solidigm Explains: Why GPU Utilization Drops Without the Right Storage
from The Ravit Show · host Ravit Jain
Everyone at NVIDIA GTC is talking about GPUs. But my conversation with Greg Matson from Solidigm was a good reminder. AI does not run on GPUs alone. It runs on data. And how fast you can move that data. What stood out is how much pressure new NVIDIA systems are putting on storage. The demand is not just for capacity anymore, but for performance and efficiency at a completely different level.Solidigm is right in the middle of this shift. They are working with NVIDIA on things like liquid-cooled SSDs inside GPU systems and supporting new innovations like context memory extension. One insight that really stayed with me. If you lose context, GPU utilization can drop from 85% to 40%.That is a massive hit. Which means storage is no longer just a backend problem. It directly impacts performance, cost, and scale. We also talked about where this is going.Bigger drives, better efficiency, and designs that allow more GPUs to run within the same power limits.This is the part of the AI stack that does not get enough attention. But it might be the one that decides how far AI can actually scale.#data #ai #nvidiagtc #solidigm #theravitshow
What this episode covers
Everyone at NVIDIA GTC is talking about GPUs. But my conversation with Greg Matson from Solidigm was a good reminder. AI does not run on GPUs alone. It runs on data. And how fast you can move that data. What stood out is how much pressure new NVIDIA systems are putting on storage. The demand is not just for capacity anymore, but for performance and efficiency at a completely different level.Solidigm is right in the middle of this shift. They are working with NVIDIA on things like liquid-cooled SSDs inside GPU systems and supporting new innovations like context memory extension. One insight that really stayed with me. If you lose context, GPU utilization can drop from 85% to 40%.That is a massive hit. Which means storage is no longer just a backend problem. It directly impacts performance, cost, and scale. We also talked about where this is going.Bigger drives, better efficiency, and designs that allow more GPUs to run within the same power limits.This is the part of the AI stack that does not get enough attention. But it might be the one that decides how far AI can actually scale.#data #ai #nvidiagtc #solidigm #theravitshow
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Solidigm Explains: Why GPU Utilization Drops Without the Right Storage
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