AI chip race: Google says its Tensor chips compute faster than Nvidia's A100

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AI chip race: Google says its Tensor chips compute faster than Nvidia's A100
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It also says that it has a healthy pipeline for chips in the future.

reported in 2021 that Google used AI to design its TPUs. Google claimed that the design process was completedFor most things associated with AI these days, product iterations occur rapidly, and the TPU is currently in its fourth generation. As Microsoft

to power OpenAI's research requirement, Google also put together 4,000 TPUs to make its supercomputer.Since these supercomputers are assigned massive tasks that a single chip cannot complete, the thousands of processing centers need to communicate among themselves. In a recent scientific paper, Google claimed it had custom-developed optical switches.

Google's PaLM model, the largest model it has publicly spoken about, was trained using a supercomputer consisting of 4,000 connected TPUs and a processing time of over 50 days. Google claims that its supercomputer can reconfigure connections between the chips on the fly, allowing it to extract performance gains from the assembly.Google also claimed in the paper that its TPUs are 1.7 times faster than the A100 chips from Nvidia, which power most AI applications. The chips are also 1.

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