Everything thats in the blog post is basically well known already. Google publishes papers and gives talks about their TPUs. Many details are lacking though, and require some assumptions/best guesses. Jax and XLA are (partially) open source and give clues about how TPUs work under the hood as well.
This is not the only way though. TPUs are available to companies operating on GCP as an alternative to GPUs with a different price/performance point. That is another way to get hands-on experience with TPUs.
There's a pretty detailed description of TPUs in the latest edition of Hennessy's Computer Architecture. (Hennessy was also involved with the design of the early TPU architectures if I recall right.)
Everything thats in the blog post is basically well known already. Google publishes papers and gives talks about their TPUs. Many details are lacking though, and require some assumptions/best guesses. Jax and XLA are (partially) open source and give clues about how TPUs work under the hood as well.
https://arxiv.org/abs/2304.01433
https://jax-ml.github.io/scaling-book/
From the acknowledgment at the end, I guess the author has access to TPUs through https://sites.research.google/trc/about/
This is not the only way though. TPUs are available to companies operating on GCP as an alternative to GPUs with a different price/performance point. That is another way to get hands-on experience with TPUs.
A quick free way to access TPUs is through https://colab.research.google.com, Runtime / Change Runtime Type / v2-8 TPU
There's a pretty detailed description of TPUs in the latest edition of Hennessy's Computer Architecture. (Hennessy was also involved with the design of the early TPU architectures if I recall right.)