Top 5 Reasons why CPU is the Best Processor for AI Inference
By Ronan Naughton, Arm
Advanced artificial intelligence (AI), like generative AI, is enhancing all our smart devices. However, a common misconception is that these AI workloads can only be processed in the cloud and data center. In fact, the majority of AI inference workloads, which are cheaper and faster to run than training, can be processed at the edge – on the actual devices.
The availability and growing AI capabilities of the CPU across today’s devices are helping to push more AI inference processing to the edge. While heterogeneous computing approaches provide the industry with the flexibility to use different computing components – including the CPU, GPU, and NPU – for different AI use cases and demands, AI inference in edge computing is where the CPU shines.
With this in mind, here are the top five reasons why the CPU is the best target for AI inference workloads.
To read the full article, click here
Related Semiconductor IP
- LDO for CPU Cores on TSMC CLN3P-CLN3X
- LDO for CPU Cores on TSMC CLN3E
- LDO for CPU Cores on TSMC CLN2P
- I3C Controller IP – I3C / I2C Slave, Configure User Registers, no CPU Host Required
- I3C Controller IP – I3C / I2C Slave, SCL Clock only, Configure User Registers, no CPU Host Required
Related White Papers
- Why Software is Critical for AI Inference Accelerators
- AI Edge Inference is Totally Different to Data Center
- Building security into an AI SoC using CPU features with extensions
- The Expanding Markets for Edge AI Inference