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Types of Hardware Acceleration

  • Book Excerpt from "Generative AI in C++"
  • by David Spuler, Ph.D.

Types of Hardware Acceleration

There are lots of different types of silicon chips available for your AI engine. The basic types of hardware chips are:

  • Central Processing Unit (CPU)
  • Graphics Processing Unit (GPU)
  • Tensor Processing Unit (TPU)
  • Application-Specific Integrated Circuit (ASIC)
  • Field-Programmable Gate Array (FPGA)

If you want to build your own hardware, and there are plenty of research papers that do, then use an FPGA or ASIC. Even prior to the AI hype, ASICs proved their value in the Bitcoin mining boom, and FPGAs were commonly behind Azure, AWS and GCP, particularly around security/data protection.

If you're not a hardware designer, you're more likely to want the main CPU and GPU options. CPU parallelism is via AVX or Arm Neon SIMD instructions. For GPUs, you're most likely looking at an NVIDIA chip, from the P100 at the low end to the H100 at the top end (with V100 or A100 in the middle). Alternatively, the TPU is a special custom AI chip created by Google, and is in the same vein as other GPU chips.

 

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