Trillium TPU

The sixth-generation Tensor Processing Unit from Google, providing exceptional performance for AI workloads.

CommonProductProductivityMachine LearningHigh-Performance Computing

Trillium TPU is Google Cloud's sixth-generation Tensor Processing Unit (TPU), specifically designed for AI workloads, offering enhanced performance and cost-effectiveness. As a key component of Google Cloud's AI Hypercomputer, it supports large-scale AI model training, fine-tuning, and inference through an integrated hardware system, open software, leading machine learning frameworks, and flexible consumption models. Trillium TPU marks a significant advancement in AI, with impressive improvements in performance, cost-efficiency, and sustainability.

Over 4 times the training performance improvement compared to the previous generation.
Up to 3 times the increase in inference throughput.
67% enhancement in energy efficiency.
4.7 times peak computational performance improvement per chip.
Doubling of high-bandwidth memory (HBM) capacity.
Doubling of inter-chip connectivity (ICI) bandwidth.
Deployment of up to 100K Trillium chips in a single Jupiter network architecture.
Up to 2.5 times improvement in training performance per dollar and up to 1.4 times improvement in inference performance per dollar.

\The target audience for Trillium TPU includes AI researchers
developers
and enterprises
particularly those organizations that require handling large-scale AI model training and inference. Its powerful performance and cost-effectiveness make it an ideal choice for businesses and researchers seeking efficient and scalable AI solutions.\

AI21 Labs utilized Trillium TPU to accelerate the development of its Mamba and Jamba language models
providing more powerful AI solutions.
Google trained its latest Gemini 2.0 AI model using Trillium TPUs
showcasing its high performance in AI model training.
Trillium TPU excels in multi-step inference tasks

1. Log in to the Google Cloud platform and access the Trillium TPU service.
2. Create or select a project
ensuring it has the necessary permissions to use Trillium TPU.
3. Configure the Trillium TPU resources as needed
including the number of chips and network architecture.

Visit

Trillium TPU Visit Over Time

Monthly Visits

33042267

Bounce Rate

36.27%

Page per Visit

9.6

Visit Duration

00:08:26

Trillium TPU Visit Trend

Trillium TPU Visit Geography

Trillium TPU Traffic Sources

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