Google Launches TPU v4 AI Chips

By Todd R. Weiss

May 20, 2021

Google CEO Sundar Pichai spoke for only one minute and 42 seconds about the company’s latest TPU v4 Tensor Processing Units during his keynote at the Google I/O virtual conference this week, but it may have been the most important and awaited news from the event.

With the new release, the company has boosted the performance of its TPU hardware by more than two times over the previous TPU v3 chips, bringing critical new power and promise to machine learning training speeds on the Google Cloud Platform.

“Our compute infrastructure is how we drive and sustain these [AI and ML] advances and Tensor Processing Units are a big part of that,” said Pichai during the almost two-hour-long keynote on May 18 (Tuesday). “Today I’m excited to announce our next generation, the TPU v4. TPUs are connected together into supercomputers, called pods. A single v4 pod contains 4,096 v4 chips, and each pod has 10x the interconnect bandwidth per chip at scale, compared to any other networking technology.”

Google CEO Sundar Pichai announcing TPU v4 at Google I/O 2021.

The resulting computing power of the new TPUs means that one TPU pod of v4 chips can deliver more than one exaflops of floating point performance, said Pichai. The performance metrics are based on Google’s custom floating point format, called “Brain Floating Point Format,” or bfloat16.

The new TPU v4 infrastructure, which will be available to Google Cloud customers later this year, is the fastest system ever deployed at Google, which Pichai called “a historic milestone.”

Creating an exaflops of computing power previously required a custom-built supercomputer, he said. “But we already have many of these deployed today, and we’ll soon have dozens of TPU v4 pods in our datacenters, many of which will be operating at or near 90 percent carbon-free energy. It’s tremendously exciting to see this pace of innovation.”

Google’s previous version TPU 3.0 was unveiled in 2018.

TPUs are Google’s custom-developed application-specific integrated circuits (ASICs) which are used to accelerate ML workloads. Developers can use Google Cloud TPUs and Google’s TensorFlow open source machine learning software library to run their ML workloads. TensorFlow was developed and first released by Google in 2015.

Google Cloud TPU is designed to help researchers, developers and businesses build TensorFlow compute clusters that can use CPUs, GPUs and TPUs as needed. TensorFlow APIs allow users to run replicated models on Cloud TPU hardware, while TensorFlow applications can access TPU nodes from containers, instances or services on Google Cloud.

Several AI analysts were quick to tout the TPU v4 news and what it will mean for enterprises that are faced with constantly growing ML training demands.

“If you’re trying to train a large AI/ML system, and you are using Google’s TensorFlow specifically, this will be a big deal,” Jack E. Gold, president and principal analyst with J. Gold Associates, told EnterpriseAI. “There is never enough processing power when large models are being trained, with some taking days or weeks to run on current systems available in the cloud, and mostly based on highly parallel GPUs. And this can be very costly in terms of cloud costs and power.”

What Google has done in response with its TPUs is to build chips that are highly optimized for TensorFlow-based modeling to expedite the training of models, especially those that must be updated often or that use large data sets, said Gold.

“So, what Google is doing here with its v4 chip is to dramatically increase the compute horsepower available, and reduce time to model significantly,” said Gold. “They are also enabling much larger models to run in a reasonable amount of time. But equally importantly they are reducing the amount of power per model – since if the models run faster, they use less total power. And that’s also good for their cloud datacenters costs, as well as just sheer capacity to handle more users.”

And by using Google’s own TPUs, this is also a move by the company to continue to substitute its own processors for those of other vendors, he said. “Google wants to stay ahead of the others like AWS and Microsoft, that are also building their own accelerators for their AI cloud-based services.”

Gold also noted that since Google does a lot of its own AI/ML/DL modeling that anything the company can do to enhance its own internal needs with additional capabilities is a big win for them. “It’s not just about supporting external customers – it’s also about their own requirements,” he said.

Charles King, principal analyst with Pund-IT, said that Google’s ability to double the performance of the previous v3 chips while also achieving exascale performance in a single V4 pod are both impressive.

“It’s a notable achievement that demonstrates the company’s technical acumen and its willingness to continue funding chip development,” said King. It’s also important for the company’s customers, he added.

“Absolutely, since these new chips will be powering AI-related workloads and services offered in Google Cloud,” said King. “If Google can deliver superior performance at highly competitive prices, it could diminish the value of competitors’ services.”

Holger Mueller, principal analyst at Constellation Research, said the TPU v4 news was “one of the most exciting announcements of Google I/O … as the company builds out its lead with algorithms on silicon with TPU v4.”

With this development, Google keeps building its lead on AI compute over AWS and Microsoft Azure, Mueller said. “[This is the] first architecture to reach an exaflops – and AI needs it. When you do it Google-style… the faster and cheaper AI will win in business and government, including with the military.”

Another analyst, Karl Freund, founder and principal analyst for machine learning, HPC and AI with Cambrian AI Research, said that early benchmarks are promising for the new TPUs.

“TPU v4 looks like a winner, based on early MLPerf benchmarks,” said Freund. “We await final benchmarks which I expect to see this summer when we get closer to the announcement of availability and pricing later this year. It has been a much longer time coming compared to earlier TPUs but may well be worth the wait.”

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Q&A with Google’s Bill Magro, an HPCwire Person to Watch in 2021

June 11, 2021

Last Fall Bill Magro joined Google as CTO of HPC, a newly created position, after two decades at Intel, where he was responsible for the company's HPC strategy. This interview was conducted by email at the beginning of A Read more…

A Carbon Crisis Looms Over Supercomputing. How Do We Stop It?

June 11, 2021

Supercomputing is extraordinarily power-hungry, with many of the top systems measuring their peak demand in the megawatts due to powerful processors and their correspondingly powerful cooling systems. As a result, these Read more…

Honeywell Quantum and Cambridge Quantum Plan to Merge; More to Follow?

June 10, 2021

Earlier this week, Honeywell announced plans to merge its quantum computing business, Honeywell Quantum Solutions (HQS), which focuses on trapped ion hardware, with the U.K.-based Cambridge Quantum Computing (CQC), which Read more…

ISC21 Keynoter Xiaoxiang Zhu to Deliver a Bird’s-Eye View of a Changing World

June 10, 2021

ISC High Performance 2021 – once again virtual due to the ongoing pandemic – is swiftly approaching. In contrast to last year’s conference, which canceled its in-person component with a couple months’ notice, ISC Read more…

Xilinx Expands Versal Chip Family With 7 New Versal AI Edge Chips

June 10, 2021

FPGA chip vendor Xilinx has been busy over the last several years cranking out its Versal AI Core, Versal Premium and Versal Prime chip families to fill customer compute needs in the cloud, datacenters, networks and more. Now Xilinx is expanding its reach to the booming edge... Read more…

AWS Solution Channel

Building highly-available HPC infrastructure on AWS

Reminder: You can learn a lot from AWS HPC engineers by subscribing to the HPC Tech Short YouTube channel, and following the AWS HPC Blog channel. Read more…

Space Weather Prediction Gets a Supercomputing Boost

June 9, 2021

Solar winds are a hot topic in the HPC world right now, with supercomputer-powered research spanning from the Princeton Plasma Physics Laboratory (which used Oak Ridge’s Titan system) to University College London (which used resources from the DiRAC HPC facility). One of the larger... Read more…

A Carbon Crisis Looms Over Supercomputing. How Do We Stop It?

June 11, 2021

Supercomputing is extraordinarily power-hungry, with many of the top systems measuring their peak demand in the megawatts due to powerful processors and their c Read more…

Honeywell Quantum and Cambridge Quantum Plan to Merge; More to Follow?

June 10, 2021

Earlier this week, Honeywell announced plans to merge its quantum computing business, Honeywell Quantum Solutions (HQS), which focuses on trapped ion hardware, Read more…

ISC21 Keynoter Xiaoxiang Zhu to Deliver a Bird’s-Eye View of a Changing World

June 10, 2021

ISC High Performance 2021 – once again virtual due to the ongoing pandemic – is swiftly approaching. In contrast to last year’s conference, which canceled Read more…

Xilinx Expands Versal Chip Family With 7 New Versal AI Edge Chips

June 10, 2021

FPGA chip vendor Xilinx has been busy over the last several years cranking out its Versal AI Core, Versal Premium and Versal Prime chip families to fill customer compute needs in the cloud, datacenters, networks and more. Now Xilinx is expanding its reach to the booming edge... Read more…

What is Thermodynamic Computing and Could It Become Important?

June 3, 2021

What, exactly, is thermodynamic computing? (Yes, we know everything obeys thermodynamic laws.) A trio of researchers from Microsoft, UC San Diego, and Georgia Tech have written an interesting viewpoint in the June issue... Read more…

AMD Introduces 3D Chiplets, Demos Vertical Cache on Zen 3 CPUs

June 2, 2021

At Computex 2021, held virtually this week, AMD showcased a new 3D chiplet architecture that will be used for future high-performance computing products set to Read more…

Nvidia Expands Its Certified Server Models, Unveils DGX SuperPod Subscriptions

June 2, 2021

Nvidia is busy this week at the virtual Computex 2021 Taipei technology show, announcing an expansion of its nascent Nvidia-certified server program, a range of Read more…

Using HPC Cloud, Researchers Investigate the COVID-19 Lab Leak Hypothesis

May 27, 2021

At the end of 2019, strange pneumonia cases started cropping up in Wuhan, China. As Wuhan (then China, then the world) scrambled to contain what would, of cours Read more…

AMD Chipmaker TSMC to Use AMD Chips for Chipmaking

May 8, 2021

TSMC has tapped AMD to support its major manufacturing and R&D workloads. AMD will provide its Epyc Rome 7702P CPUs – with 64 cores operating at a base cl Read more…

Intel Launches 10nm ‘Ice Lake’ Datacenter CPU with Up to 40 Cores

April 6, 2021

The wait is over. Today Intel officially launched its 10nm datacenter CPU, the third-generation Intel Xeon Scalable processor, codenamed Ice Lake. With up to 40 Read more…

Berkeley Lab Debuts Perlmutter, World’s Fastest AI Supercomputer

May 27, 2021

A ribbon-cutting ceremony held virtually at Berkeley Lab's National Energy Research Scientific Computing Center (NERSC) today marked the official launch of Perlmutter – aka NERSC-9 – the GPU-accelerated supercomputer built by HPE in partnership with Nvidia and AMD. Read more…

CERN Is Betting Big on Exascale

April 1, 2021

The European Organization for Nuclear Research (CERN) involves 23 countries, 15,000 researchers, billions of dollars a year, and the biggest machine in the worl Read more…

Google Launches TPU v4 AI Chips

May 20, 2021

Google CEO Sundar Pichai spoke for only one minute and 42 seconds about the company’s latest TPU v4 Tensor Processing Units during his keynote at the Google I Read more…

Iran Gains HPC Capabilities with Launch of ‘Simorgh’ Supercomputer

May 18, 2021

Iran is said to be developing domestic supercomputing technology to advance the processing of scientific, economic, political and military data, and to strengthen the nation’s position in the age of AI and big data. On Sunday, Iran unveiled the Simorgh supercomputer, which will deliver.... Read more…

HPE Launches Storage Line Loaded with IBM’s Spectrum Scale File System

April 6, 2021

HPE today launched a new family of storage solutions bundled with IBM’s Spectrum Scale Erasure Code Edition parallel file system (description below) and featu Read more…

Quantum Computer Start-up IonQ Plans IPO via SPAC

March 8, 2021

IonQ, a Maryland-based quantum computing start-up working with ion trap technology, plans to go public via a Special Purpose Acquisition Company (SPAC) merger a Read more…

Leading Solution Providers

Contributors

10nm, 7nm, 5nm…. Should the Chip Nanometer Metric Be Replaced?

June 1, 2020

The biggest cool factor in server chips is the nanometer. AMD beating Intel to a CPU built on a 7nm process node* – with 5nm and 3nm on the way – has been i Read more…

Julia Update: Adoption Keeps Climbing; Is It a Python Challenger?

January 13, 2021

The rapid adoption of Julia, the open source, high level programing language with roots at MIT, shows no sign of slowing according to data from Julialang.org. I Read more…

AMD Launches Epyc ‘Milan’ with 19 SKUs for HPC, Enterprise and Hyperscale

March 15, 2021

At a virtual launch event held today (Monday), AMD revealed its third-generation Epyc “Milan” CPU lineup: a set of 19 SKUs -- including the flagship 64-core, 280-watt 7763 part --  aimed at HPC, enterprise and cloud workloads. Notably, the third-gen Epyc Milan chips achieve 19 percent... Read more…

Can Deep Learning Replace Numerical Weather Prediction?

March 3, 2021

Numerical weather prediction (NWP) is a mainstay of supercomputing. Some of the first applications of the first supercomputers dealt with climate modeling, and Read more…

Livermore’s El Capitan Supercomputer to Debut HPE ‘Rabbit’ Near Node Local Storage

February 18, 2021

A near node local storage innovation called Rabbit factored heavily into Lawrence Livermore National Laboratory’s decision to select Cray’s proposal for its CORAL-2 machine, the lab’s first exascale-class supercomputer, El Capitan. Details of this new storage technology were revealed... Read more…

GTC21: Nvidia Launches cuQuantum; Dips a Toe in Quantum Computing

April 13, 2021

Yesterday Nvidia officially dipped a toe into quantum computing with the launch of cuQuantum SDK, a development platform for simulating quantum circuits on GPU-accelerated systems. As Nvidia CEO Jensen Huang emphasized in his keynote, Nvidia doesn’t plan to build... Read more…

Microsoft to Provide World’s Most Powerful Weather & Climate Supercomputer for UK’s Met Office

April 22, 2021

More than 14 months ago, the UK government announced plans to invest £1.2 billion ($1.56 billion) into weather and climate supercomputing, including procuremen Read more…

African Supercomputing Center Inaugurates ‘Toubkal,’ Most Powerful Supercomputer on the Continent

February 25, 2021

Historically, Africa hasn’t exactly been synonymous with supercomputing. There are only a handful of supercomputers on the continent, with few ranking on the Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire