To run complex AI training and inference workloads, today’s AI data centers need huge amounts of compute, storage and memory bandwidth, power distribution, and networking capabilities – all provided by the full stack of chip technologies. Each of these chip technologies is essential to driving America’s AI buildout, while supply disruptions in any of these areas could risk hampering this buildout. Chips in AI data centers include:
• Advanced logic chips, such as AI accelerators, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), central processing units (CPUs), data processing units (DPUs), and networking chips.
• Memory, such as high-bandwidth memory (HBM), both dynamic and static random-access memory (DRAM and SRAM), and non-volatile flash memory (NAND).
• Analog and foundational chips, such as power chips, transceivers, controllers, and sensors.
