HomeIronwood is Google’s newest AI accelerator chip
At this week's Cloud Next conference, Google pulled back the curtain on its latest TPU AI accelerator chip, dubbed Ironwood. This seventh-generation marvel marks a significant shift as it's the first TPU specifically tailored for AI model inference. Set to roll out later this year for Google Cloud users, Ironwood will be available in two powerhouse configurations: a 256-chip cluster and a massive 9,216-chip cluster.
Amin Vahdat, Google Cloud VP, shared his excitement in a blog post, saying, "Ironwood is our most powerful, capable, and energy-efficient TPU yet. And it's purpose-built to power thinking, inferential AI models at scale." It's clear that Google is aiming high with this new chip.
The AI accelerator market is heating up, with Nvidia leading the charge, but don't count out the tech giants. Amazon is in the game with its Trainium, Inferentia, and Graviton chips, available through AWS, while Microsoft is pushing forward with Azure instances powered by its Maia 100 AI chip.
Image Credits:Google
According to Google's internal benchmarks, Ironwood packs a punch with 4,614 TFLOPs of peak computing power. Each chip comes equipped with 192GB of dedicated RAM, boasting a bandwidth that's nearing 7.4 Tbps. That's some serious firepower!
Ironwood isn't just about brute force; it's smart, too. It features an advanced core called SparseCore, designed to handle the kind of data you'd see in sophisticated ranking and recommendation systems—like those that suggest what clothes might catch your eye. Google's engineers have also worked to reduce data movement and latency within the chip, which should translate to significant energy savings.
Looking ahead, Google plans to weave Ironwood into its AI Hypercomputer, a modular computing cluster within Google Cloud. This integration is on the horizon, and Vahdat is confident, stating, "Ironwood represents a unique breakthrough in the age of inference, with increased computation power, memory capacity, networking advancements, and reliability."
Updated 10:45 a.m. Pacific: A previous version of this story mistakenly referred to Microsoft’s Cobalt 100 as an AI chip. It's actually a general-purpose chip; the correct AI chip from Microsoft is the Maia 100. We've made the necessary correction.
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Comments (10)
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![EricRoberts]()
Ironwood、推論専用か。GoogleのTPP進化は速いね。モデルサイズが巨大化する中、推論コストの削減は必須課題だし、この方向性は正しいと思う。ただ、既存のGPUユーザーはどうなるのか？競合他社との価格競争が激化しそうだ。来年の展開に期待しつつも、ベンダーロックインへの懸念は拭えないな。🤖💻
![JackWilson]()
So Google's Ironwood is specifically for inference? Interesting that they're moving away from training. I wonder how it'll compete with NVIDIA's H100... 🧠
![DouglasAnderson]()
Interesting! Google keeps pushing the AI hardware envelope. While specialized inference chips like Ironwood are a big deal for cloud efficiency, I can't help but wonder about the long-term environmental impact of this never-ending race for more powerful, energy-intensive silicon. Are we building a monster we can't power sustainably? 🤔 The focus should be on both performance and green computing.
![DouglasScott]()
Ironwood sounds like a beast for AI inference! Google’s really stepping up their game, but I wonder how it stacks against Nvidia’s chips. Excited to see real-world benchmarks! 🚀
![KeithNelson]()
Google's Ironwood chip sounds like a game-changer for AI inference! Excited to see how it stacks up against Nvidia's offerings. 🚀
![BrianWalker]()
GoogleのIronwoodチップはクールに聞こえますが、私の日常のAI使用がどのように変わるかはわかりません。推論に特化しているんですよね？Google Cloudに登場したらどうなるか見てみましょう。期待しています！🤞
At this week's Cloud Next conference, Google pulled back the curtain on its latest TPU AI accelerator chip, dubbed Ironwood. This seventh-generation marvel marks a significant shift as it's the first TPU specifically tailored for AI model inference. Set to roll out later this year for Google Cloud users, Ironwood will be available in two powerhouse configurations: a 256-chip cluster and a massive 9,216-chip cluster.
Amin Vahdat, Google Cloud VP, shared his excitement in a blog post, saying, "Ironwood is our most powerful, capable, and energy-efficient TPU yet. And it's purpose-built to power thinking, inferential AI models at scale." It's clear that Google is aiming high with this new chip.
The AI accelerator market is heating up, with Nvidia leading the charge, but don't count out the tech giants. Amazon is in the game with its Trainium, Inferentia, and Graviton chips, available through AWS, while Microsoft is pushing forward with Azure instances powered by its Maia 100 AI chip.
According to Google's internal benchmarks, Ironwood packs a punch with 4,614 TFLOPs of peak computing power. Each chip comes equipped with 192GB of dedicated RAM, boasting a bandwidth that's nearing 7.4 Tbps. That's some serious firepower!
Ironwood isn't just about brute force; it's smart, too. It features an advanced core called SparseCore, designed to handle the kind of data you'd see in sophisticated ranking and recommendation systems—like those that suggest what clothes might catch your eye. Google's engineers have also worked to reduce data movement and latency within the chip, which should translate to significant energy savings.
Looking ahead, Google plans to weave Ironwood into its AI Hypercomputer, a modular computing cluster within Google Cloud. This integration is on the horizon, and Vahdat is confident, stating, "Ironwood represents a unique breakthrough in the age of inference, with increased computation power, memory capacity, networking advancements, and reliability."
Updated 10:45 a.m. Pacific: A previous version of this story mistakenly referred to Microsoft’s Cobalt 100 as an AI chip. It's actually a general-purpose chip; the correct AI chip from Microsoft is the Maia 100. We've made the necessary correction.
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Ironwood、推論専用か。GoogleのTPP進化は速いね。モデルサイズが巨大化する中、推論コストの削減は必須課題だし、この方向性は正しいと思う。ただ、既存のGPUユーザーはどうなるのか？競合他社との価格競争が激化しそうだ。来年の展開に期待しつつも、ベンダーロックインへの懸念は拭えないな。🤖💻
So Google's Ironwood is specifically for inference? Interesting that they're moving away from training. I wonder how it'll compete with NVIDIA's H100... 🧠
Interesting! Google keeps pushing the AI hardware envelope. While specialized inference chips like Ironwood are a big deal for cloud efficiency, I can't help but wonder about the long-term environmental impact of this never-ending race for more powerful, energy-intensive silicon. Are we building a monster we can't power sustainably? 🤔 The focus should be on both performance and green computing.
Ironwood sounds like a beast for AI inference! Google’s really stepping up their game, but I wonder how it stacks against Nvidia’s chips. Excited to see real-world benchmarks! 🚀
Google's Ironwood chip sounds like a game-changer for AI inference! Excited to see how it stacks up against Nvidia's offerings. 🚀
GoogleのIronwoodチップはクールに聞こえますが、私の日常のAI使用がどのように変わるかはわかりません。推論に特化しているんですよね？Google Cloudに登場したらどうなるか見てみましょう。期待しています！🤞
