Spend less on HPC/AI storage

(And more on compute)


With the convergence of classical HPC and AI in the exascale era, storage costs are eating more of high-performance computing budgets every day. With the data demands of applications like machine learning, computer-aided engineering, automated trading, drug discovery, and fraud protection, that’s only going to get worse. That means you will need to choose between ballooning the budget or crimping compute costs for your HPC future.

Or do you? Join Uli Plechschmidt of HPE who will explain to the Reg’s Tim Phillips why HPE is advising you to spend less on HPC/AI storage, and more on CPU/GPU compute, and the cunning architectures that means this will not compromise outcomes.

You will find out:

  • The costs of staying with legacy storage architectures
  • The potential of parallel HPC/AI storage systems
  • Cost-effective infrastructure for your needs

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