Research history Compute

Google's first-generation Tensor Processing Unit is a custom chip built to speed up neural-network inference in its data centers. Deployed in 2015 and revealed in 2016, it showed that dedicated accelerators could beat CPUs and GPUs on cost-performance.

A consumer graphics card NVIDIA released in November 2010 on its Fermi architecture. Two of them, each with 3 GB of memory, later trained AlexNet, the network that won ILSVRC-2012 and which NVIDIA's timeline credits with sparking the era of modern AI.

The Tesla P100, announced by NVIDIA in April 2016, was the first data-center GPU on the Pascal architecture, and the first to combine stacked HBM2 memory, half-precision math aimed at deep learning and the NVLink interconnect.

NVIDIA's Tesla K80 is a dual-GPU data-center accelerator announced in November 2014, putting two GK210 chips, 24 GB of memory and up to 8.74 teraflops of single-precision performance on one 300 W board.

An AI processor from Cerebras Systems that keeps an entire silicon wafer as one chip, holding more than 1.2 trillion transistors and 400,000 cores; the first of a line that reached WSE-3 in 2024.