CPU + GPU: Why AI platform engineering is a heterogeneous infrastructure problem
Accelerators provide much of the compute behind model training and inference, so the focus is understandable.
Useful takeaways from this story.
Accelerators provide much of the compute behind model training and inference, so the focus is understandable.
A production AI workload rarely starts and ends on a GPU.
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The useful part
Accelerators provide much of the compute behind model training and inference, so the focus is understandable. AI infrastructure conversations often start with GPUs. A production AI workload rarely starts and ends on a GPU.
How it works
- A production AI workload rarely starts and ends on a GPU.
Details worth keeping
AI infrastructure conversations often start with GPUs.
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