Datacenter Chip Market Trends

Datacenter Chip Market Trends

Specialized processing functions have changed the data center chip market, with an increasing number of AI and machine learning workloads. Organizations are constantly utilizing AI and machine learning models for processing large volumes of data via processing chips, so to optimize themselves during operation. Some of the features found in data center chips meant for AI and ML applications include high parallelism, low precision arithmetic, purpose-built AI processors as well as dedicated accelerators among them TPUs or GPUs. For instance, in March 2022, NVIDIA launched a H100 data center chip designed to train large language models (LLMs) four times faster than A100; it also gives responses to user prompts approximately 30 times faster than its previous version-A100.
 

The transition to hyperscale data centers is an ongoing trend in the market for chips used in data centers, which has been driven by the rapid explosion of data that is generated and processed globally. Technology titans such as Google, Amazon and Facebook operate hyperscale data centers which require specific chips that can handle heavy workloads efficiently. They are made with scalability, energy efficiency as well as performance optimization to fit into hyperscale architectures, giving them a competitive edge over traditional microprocessors. Expansion of hyperscale datacenters to catch up with increasing data requirements has necessitated the development of new world-class ICs for this sector.