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Trillium TPU

Google's sixth-generation tensor processing unit delivers superior AI workload performance.

#AI
#machine learning
#high performance computing
#cloud computing
#Google Cloud
Trillium TPU

Product Details

Trillium TPU is Google Cloud’s sixth-generation Tensor Processing Unit (TPU) designed specifically for AI workloads, delivering enhanced performance and cost-effectiveness. As a key component of the Google Cloud AI Hypercomputer, it supports the training, fine-tuning and inference of large-scale AI models through integrated hardware systems, open software, leading machine learning frameworks and flexible consumption models. Trillium TPU has significantly improved performance, cost efficiency and sustainability, and is an important advancement in the field of AI.

Main Features

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More than 4 times the training performance improvement of the previous generation.
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Up to 3x increased inference throughput.
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Energy efficiency increased by 67%.
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Peak computing performance per chip is increased by 4.7 times.
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High-bandwidth memory (HBM) capacity doubled.
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Inter-chip interconnect (ICI) bandwidth doubled.
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100K Trillium chips can be deployed in a single Jupiter network structure.
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Training performance is improved by up to 2.5 times per dollar, and inference performance is improved by up to 1.4 times per dollar.

How to Use

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1. Log in to the Google Cloud platform and access the Trillium TPU service.
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2. Create or select a project and ensure that the project has permission to use Trillium TPU.
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3. Configure Trillium TPU resources as needed, including the number of chips and network structure.
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4. Deploy the AI ​​model to Trillium TPU and start training or inference tasks.
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5. Monitor task performance and use tools provided by Google Cloud to optimize model and resource usage.
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6. Adjust Trillium TPU resource configuration according to business needs to achieve the best balance between cost and performance.
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7. After completing the AI ​​task, release Trillium TPU resources that are no longer needed to save costs.

Target Users

Trillium TPU is targeted at AI researchers, developers and enterprises, especially those organizations that need to handle large-scale AI model training and inference. Its strong performance and cost-effectiveness make it ideal for enterprises and researchers who need efficient, scalable AI solutions.

Examples

AI21 Labs uses Trillium TPU to accelerate the development of its Mamba and Jamba language models, providing more powerful AI solutions.

Google used Trillium TPUs to train the latest Gemini 2.0 AI model, demonstrating its high performance in AI model training.

Trillium TPU excels in multi-step inference tasks, providing significant inference performance improvements for image diffusion and large language models.

Quick Access

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Categories

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› Model training and deployment
› GPU

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