Google announced that Ironwood, its seventh generation of TPUs (tensor processing units), will be made generally available in the coming few weeks.
This means that Google Cloud customers will be able to utilise TPU v7 for their AI workloads.
The chip is claimed to offer a ten-fold peak performance improvement over TPU v5, and 4x better performance per chip for both training and inference workloads compared to TPU v6.
TPUs are chips that are specifically designed to handle AI workloads. Besides providing it for customers on Google Cloud, the company also uses it to train and deploy the Gemini, Imagen, Veo and other families of its AI models.
Additionally, large-scale Google Cloud customers have also utilised TPUs for their AI workloads.
Anthropic, the company behind the Claude family of AI models, has long utilised TPUs via Google Cloud for its workloads and has recently expanded its partnership with Google to deploy over 1 million new TPUs.
“With Ironwood, we can scale up to 9,216 chips in a superpod linked with breakthrough Inter-Chip Interconnect (ICI) networking at 9.6 Tb/s,” said Google in the announcement. This also enables access to 1.77 petabytes (PBs) of shared High Bandwidth Memory (HBM).
TPUs are also built to offer better performance efficiency compared to GPUs. A study from Google stated that TPU v4 is 1.2× to 1.7× faster than an NVIDIA A100 GPU (and uses 1.3× to 1.9× less power.
Recently, Google announced a new research Project Suncatcher, which aims to explore the feasibility of scaling AI compute in space using solar-powered satellite constellations equipped with TPUs.
According to D.A. Davidson analysts, cited by MarketWatch, combining Google’s TPU business with its DeepMind AI research unit could be valued at around $900 billion.
If Google eventually offers TPUs as hardware systems outside of Google Cloud, industry experts believe it could provide serious competition to the GPU market, including players like NVIDIA and AMD.
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