AMD's Lisa Su confirms EPYC serves as host processor for Google TPU 8tx
AMD CEO Lisa Su congratulated Google Cloud and Amin Vahdat, and confirmed AMD EPYC as the host processor for TPU 8tx, with the two sides collaborating on this. The cited original Google post states that the eighth-generation TPUs add TPU 8i Max and TPU 8tx for secure confidential inference, marking the first time Google has launched four TPU systems within the same year.
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AMD CEO publicly confirms that EPYC has become the host processor for TPU 8tx among Google's eighth-generation TPUs, highlighting the division of collaboration between the two companies in AI infrastructure.
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View original postThrilled to share a big milestone from our AI & Infrastructure team at @Google. Today we’re expanding our 8th generation TPU portfolio with: • TPU 8i Max: Built for massive context windows and the highest compute density per rack • TPU 8tx: Purpose-built for secure, confidential inference This marks the first time we’ve introduced four distinct TPU systems in a single generation, in one year. For developers, hardware is only as good as the software stack. And we want you to be able to build with TPUs as easily and efficiently as we do at Google. You can now: ↳ Run native PyTorch & Hugging Face models via TorchTPU (zero code rewrites) ↳ Cut KV transfer latency >90% with open-source TPU Sync ↳ Eliminate idle compute waste with Agent Compute Engine Read more about our newest TPUs on our blog: https://t.co/8eaFhq3jhi I look forward to connecting with builders, researchers, engineers and organizations pushing the boundaries of AI and computing!
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Thrilled to share a big milestone from our AI & Infrastructure team at @Google. Today we’re expanding our 8th generation TPU portfolio with: • TPU 8i Max: Built for massive context windows and the highest compute density per rack • TPU 8tx: Purpose-built for secure, confidential inference This marks the first time we’ve introduced four distinct TPU systems in a single generation, in one year. For developers, hardware is only as good as the software stack. And we want you to be able to build with TPUs as easily and efficiently as we do at Google. You can now: ↳ Run native PyTorch & Hugging Face models via TorchTPU (zero code rewrites) ↳ Cut KV transfer latency >90% with open-source TPU Sync ↳ Eliminate idle compute waste with Agent Compute Engine Read more about our newest TPUs on our blog: https://t.co/8eaFhq3jhi I look forward to connecting with builders, researchers, engineers and organizations pushing the boundaries of AI and computing!
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Congratulations to our friends at @googlecloud and @AminVahdat! We’re proud to partner with you, with @AMD EPYC serving as the host processor for TPU 8tx.