AI's GPU problem is actually a data delivery problem

Presented by F5As enterprises pour billions into GPU infrastructure for AI workloads, many are discovering that their expensive compute resources sit idle far more than expected. The culprit isn't the hardware. It’s the often-invisible data delivery layer between storage and compute that's starving GPUs of the information they need."While people are focusing their attention, justifiably so, on GPUs, because they're very significant investments, those are rarely the limiting factor," says Mark Menger, solutions architect at F5. "They're capable of more work. They're waiting on data."AI performance increasingly depends on an independent, programmable control point between AI frameworks and object storage — one that most enterprises haven’t deliberately architected. As AI workloads scale, bot