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Google Cloud Introduces its 6th Gen TPU “Trillium” With 4.7x Increased Compute

Google Cloud recently announced its sixth-generation custom AI chip, Trillium TPU. These new TPUs deliver significantly better performance and efficiency. Trillium TPUs are a culmination of over a decade of research and innovation by Google. Let’s take a deeper look at some of Trillium’s key capabilities and advantages.

Trillium TPU – A Peak into the New Hardware

TPUs are application-specific integrated circuits (ASICs) designed by Google for machine learning workloads. Each new generation brings significant performance gains, and Trillium is no exception. It achieves a massive 4.7x increase in peak computing performance per chip compared to the previous generation TPU v5e. This level of optimized processing power will enable the training of larger and more complex AI models faster than ever. The scaling is a result of optimizations at both the architectural and component levels.

Key Features of Trillium TPU

1. Peak Performance

Trillium delivers a massive 4.7x increase in compute performance per chip compared to the previous generation v5e TPU. This is achieved through optimizing components like the MXUs and increasing clock speeds. SparseCore also helps accelerate sparse workloads.

2. High Memory Capacity

The HBM capacity and bandwidth have both been doubled versus v5e. This allows Trillium to efficiently handle much larger models with more parameters and embedding tables during training and inference.

3. Scalable Connectivity

The Inter-Chip Interconnect (ICI) bandwidth has been doubled as well. Combined with optics and Jupiter networking, this allows seamlessly scaling workloads across thousands of TPU chips distributed across multiple pods.

4. Energy Efficiency

Despite greatly enhanced processing power, Trillium is 67% more energy efficient than v5e. This focus on sustainable supercomputing will be important as models increase in scale and complexity.

5. AI Hypercomputer Compatibility

Trillium is designed for the AI Hypercomputer architecture, with capabilities like flexibly distributing work across hundreds of connected pods with exascale network throughput.

6. Framework Support

Trillium can be easily programmed using popular frameworks like JAX, PyTorch, and TensorFlow through their XLA compiler backends. This lowers the barrier for researchers and developers.

7. Cloud Deployment

Customers can access Trillium TPUs on Google Cloud platforms like Compute Engine, Vertex AI, and AI Platform with flexible consumption models and optimized configurations.

Real-World Applications of Trillium TPUs

1. Essential AI: Reinventing Mobility with Assisted Driving

Essential AI is an autonomous vehicle startup focusing on assisted driving technologies. With Trillium TPUs, they aim to develop perception models that can seamlessly blend human and computer control for safer transportation. The chip’s high performance will allow for the training of more complex neural nets needed for navigating diverse road scenarios in real time.

2. Deep Genomics: Accelerating Drug Discovery

As a pioneer in AI for healthcare, Deep Genomics leverages multi-modal models for tasks like compound screening and target identification. Trillium will prove integral to optimizing their foundation models, helping diagnose rare diseases and slash development times for life-saving therapies. Processing genome-scale data at speed while ensuring patient privacy is crucial.

3. Nuro: Powering Next-Gen Delivery Bots

Nuro’s adorable self-driving delivery vehicles rely on AI for navigation and interaction. Trillium accelerates the training of their perception stacks, handling massive sensor inputs. This will help scale operations and embed more advanced socio tech like gestural communication with pedestrians. The faster simulation also improves the safety validation of new features.

4. Deloitte: AI Transformation for Enterprises

As a Google Cloud Partner of the Year, Deloitte deploys generative models across industries.Trillium opens up personalized advisory services, prescriptive maintenance using ML, and other productivity boosters for customers. Deloitte can now develop highly customized solutions leveraging Trillium’s massive processing power and memory in innovative ways.

Maximizing the Impact of Trillium TPU Via Partnerships

Google has formed important partnerships to maximize the impact of Trillium TPU:

1. Hugging Face Partnership

Hugging Face Partnered with Google on Optimum-TPU to streamline AI model training and serving on TPUs. This makes TPU performance accessible to all through the new library. With Trillium’s 4.7x gain, open-source models will achieve new heights. This will accelerate AI development globally.

2. Partnership with SADA

SADA, an AI consultancy and Google Cloud Partner of the Year, has 20+ years of experience in AI. They will provide expert guidance to help customers unleash the power of Trillium TPUs and AI Hypercomputer. Through optimized deployments and rapid AI integration, their partnership will dramatically grow the roi impact for many businesses.

3. Lightricks Collaboration

This company develops creative AI tools. They saw 2.5x speedups using prior TPUs. Trillium’s 4.7x boost is well-timed as they scale text-to-video models. Dynamic scheduling will also optimize batch jobs. Their work in generative media illustrates how various industries can benefit from this new generation of hardware.

What’s Next For AI?

Trillium signifies an immense milestone in the development of custom AI hardware. It represents over a decade of refinement in Google’s TPU architecture and will future-proof the next generation of deep learning. Developers, researchers, and businesses just getting started in AI now have access to leading-edge capabilities. Trillium TPUs will be available on Google Cloud later this year.  

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Picture of Faizan Ali Naqvi
Faizan Ali Naqvi

Research is my hobby and I love to learn new skills. I make sure that every piece of content that you read on this blog is easy to understand and fact checked!

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