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.
- 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
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