The Tensor Processing Unit (TPU), is a chip that is designed to accelerate the inference stage of deep neural networks. Google published a paper on Wednesday laying out the performance gains the company saw over comparable CPUs and GPUs, both in terms of raw power and the performance per watt of power consumed.
TPU was on average 15 to 30 times faster at the machine learning inference tasks tested than a comparable server-class Intel Haswell CPU or Nvidia K80 GPU. Importantly, the performance per watt of the TPU was 25 to 80 times better than what Google found with the CPU and GPU.
Driving this sort of performance increase is important for Google, considering the company’s emphasis on building machine learning applications. The gains validate the company’s focus on building machine learning hardware at a time when it’s harder to get massive performance boosts from traditional silicon.
[PC World]
