skip to main content

Introduction

Large enterprises need to make decisions on which microprocessors to deploy across multiple edge-to-cloud scenarios and provide their workforce with enough compute resources to run new generation applications making more use of artificial intelligence (AI) and heavy-duty analytics.

Highlights

  • The report introduces eleven criteria to help evaluate the right choice of microprocessor for the use cases required.

Features and Benefits

  • Learn why performance statistics alone are not enough when evaluating a microprocessor.
  • Understand the different workloads that arise in AI applications and the impact this has on compute resources.

Key questions answered

  • Why is the software stack provided with a microprocessor crucial to the successful use of the chip?
  • What are the different compute resources required for AI training and AI inference modes?

Table of contents

Ovum view

  • Summary
  • Recommendations for the enterprise
  • The complex choices to be traded off when choosing a microprocessor
  • What to look for in a new chip: detailed criteria

Appendix

  • Further reading
  • Authors