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Compute | London // Major Panel: Reading between the lines - Striking the XPU/GPU/CPU balance to adapt to AI inference workloads?

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  • Compute Hardware Stage
  • Compute
  • Open Session

Speakers

Matt Foley

Matt Foley

Director, Field Application Engineering, EMEA, AMD

GenAI is growing 800x every 2 years, but compute is growing at a rate of less than 2x and a GPU supply shortage looms, but is the rush for GPUs going to continue as AI inference becomes the dominant workload? Could CPUs act as cost-effective alternative?

Or will inference leave GPUs gathering dust?

How should you balance hardware performance in the short and long-term? Join our talk to find out:

  • Primrose Path: As inferencing makes up 85% of the AI compute problem, is the focus on GPUs over CPUs leading everyone down the wrong path?
  • Getting Lean: How will changes in model building from going bigger to higher efficiency models affect the choice of compute hardware?
  • GP4U: How to think about the rise of GPU-as-a-Service and its role in next gen AI workloads