Artificial Intelligence (AI) Chips
Context
Recently, Intel launched new Artificial Intelligence (AI) chips to provide customers with deep learning compute choices for training and inferencing in data centres.
What are AI chips?
- AI chips are built with specific architecture and have integrated AI acceleration to support deep learning-based applications.
- These chips have hardware architectures and complementary packaging, memory, storage and interconnect technologies which make it possible to infuse AI into a broad spectrum of applications.
- There are different types of AI chips such as:
- Application-specific integrated circuits (ASICs),
- Field-programmable gate arrays (FPGAs),
- Central processing units (CPUs)
- GPUs
What is Deep Learning?
|
Significance
- AI chips generally contain processor cores as well as several AI-optimised cores (depending on the scale of the chip) that are designed to work in harmony when performing computational tasks.
- The AI cores are optimised for the demands of heterogeneous enterprise-class AI workloads with low-latency inferencing, due to close integration with the other processor cores, which are designed to handle non-AI applications.
