Organizations across industries are looking to AI to turn troves of data into intelligence, powered by the latest advances in generative AI. Yet for many organizations, there is a barrier to adopting the latest models because they can be costly to train or serve. A new class of cloud GPUs is needed to lower the cost of entry for businesses that want to tap the power of AI. 

Today, we’re introducing G2, the newest addition to the Compute Engine GPU family in Google Cloud. G2 is the industry’s first cloud VM powered by the newly announced NVIDIA L4 Tensor Core GPU, and is purpose-built for large inference AI workloads like generative AI. G2 delivers cutting-edge performance-per-dollar for AI inference workloads that run on GPUs in the cloud. By switching from NVIDIA A10G GPUs to G2 instances with L4 GPUs, organizations can lower their production infrastructure costs up to 40%. We also found that customers switching from NVIDIA T4 GPUs to L4 GPUs can achieve 2x-4x better performance. As a universal GPU offering, G2 instances also help accelerate other workloads, offering significant performance improvements on HPC, graphics, and video transcoding. Currently in private preview, G2 VMs are both powerful and flexible, and scale easily from one up to eight GPUs. 

Currently organizations require end-to-end enterprise ready infrastructure that will future proof their AI and HPC initiatives for a new era. G2s will be ready to be deployed on Vertex AI, GKE, and GCE, giving customers the freedom to architect their own custom software stack to meet their performance requirements and budget. With optimized Vertex AI support for G2 VMs, AI users can tap the latest generative AI models and technologies. With an easy to use UI and automated workflows, customers can access, tune and serve modern models for video, text, images, and audio without the toil of manual optimizations. The combination of these services with the power of G2 will help customers harness the power of complex machine models for their business.

NVIDIA L4 GPUs with Ada Lovelace Architecture

G2 machine families enable machine learning customers to run their production infrastructure in the cloud for a variety of applications such as language models, image classification, object detection, automated speech recognition, and language translation. Built on the Ada Lovelace architecture with fourth-generation Tensor Cores, the NVIDIA L4 GPU provides up to 30 TFLOPS of performance for FP32, and 242 TFLOPs for FP16. Newly added FP8 support, on top of existing INT8, BFLOAT16 and TF32 capabilities, makes the L4 ideal for ML inference. 

With the latest third-generation RT Cores and DLSS 3.0 technology, G2 instances are also great for graphics-intensive workloads such as rendering and remote workstations when paired with NVIDIA RTX Virtual Workstation. NVIDIA L4 provides 3x video encoding and decoding performance, and adds new AV1 hardware-encoding capabilities. For example, G2 can enable gaming customers running game engines such as Unreal and Unity with modern graphics cards to run real-time applications. Likewise, media and entertainment customers that need GPU-enabled virtual workstations can use the L4 to create photo-realistic, high-resolution 3D content for movies, games, and AR/VR experiences using applications such as Autodesk Maya or 3D Studio Max.

What customers are saying

A handful of early customers have been testing G2 and have seen great results in real-world applications. Here are what some of them have to say about the benefits that G2 with NVIDIA L4 GPUs bring:

AppLovin

AppLovin enables developers and marketers to grow with market leading technologies. Businesses rely on AppLovin to solve their mission-critical functions with a powerful, full stack solution including user acquisition, retention, monetization and measurement.

“AppLovin serves billions of AI powered recommendations per day, so scalability and value are essential to our business,” said Omer Hasan, Vice President, Operations at AppLovin. “With Google Cloud’s G2 we’re seeing that NVIDIA L4 GPUs offer a significant increase in the scalability of our business, giving us the power to grow faster than ever before.”

WOMBO

WOMBO aims to unleash everyone’s creativity through the magic of AI, transforming the way content is created, consumed, and distributed. 

“WOMBO relies upon the latest AI technology for people to create immersive digital artwork from users’ prompts, letting them create high-quality, realistic art in any style with just an idea,” said Ben-Zion Benkhin, Co-Founder and CEO of WOMBO. “Google Cloud’s G2 instances powered by NVIDIA’s L4 GPUs will enable us to offer a better, more efficient image-generation experience for users seeking to create and share unique artwork.”

Descript

Descript’s AI-powered features and intuitive interface fuel YouTube and TikTok channels, top podcasts, and businesses using video for marketing, sales, and internal training and collaboration. Descript aims to make video a staple of every communicator’s toolkit, alongside docs and slides. 

“G2 with L4’s AI Video capabilities allow us to deploy new features augmented by natural-language processing and generative AI to create studio-quality media with excellent performance and energy efficiency” said Kundan Kumar, Head of Artificial Intelligence at Descript.

Workspot

Workspot believes that the software-as-a-service (SaaS) model is the most secure, accessible and cost-effective way to deliver an enterprise desktop and should be central to accelerating the digital transformation of the modern enterprise.

“The Workspot team looks forward to continuing to evolve our partnership with Google Cloud and NVIDIA. Our customers have been seeing incredible performance leveraging NVIDIA’s T4 GPUs. The new G2 instances with L4 GPUS through Workspot’s remote Cloud PC workstations provide 2x and higher frame rates at 1280×711 and higher resolutions” said Jimmy Chang, Chief Product Officer at Workspot.

Pricing and availability

G2 instances are currently in private preview in the following regions: us-central1, asia-southeast1 and europe-west4. Submit your request here to join the private preview, or to receive a notification as when the public preview begins. Support will be coming to Google Kubernetes Engine (GKE), Vertex AI, and other Google Cloud services as well. We’ll share G2 public availability and pricing information later in the year.

There’s a new subsea cable in town: Topaz, the first-ever fiber cable to connect Canada and Asia.

Once complete, Topaz will run from Vancouver to the small town of Port Alberni on the west coast of Vancouver Island in British Columbia, and across the Pacific Ocean to the prefectures of Mie and Ibaraki in Japan. We expect the cable to be ready for service in 2023, not only delivering low-latency access to Search, Gmail and YouTube, Google Cloud, and other Google services, but also increasing capacity to the region for a variety of network operators in both Japan and Canada.

Google is spearheading construction of the project, joined by a number of local partners in Japan and Canada to deliver the full Topaz subsea cable system. Other networks and internet service providers will be able to benefit from the cable’s additional capacity, whether for their own use or to provide to third parties. And, similar to other cables we’ve built, with Topaz we will exchange fiber pairs with partners who have systems along similar routes. This is a longstanding practice in the industry that strengthens the intercontinental network lattice for network operators, for Google, and for users around the world.

Network infrastructure investments like Topaz bring significant economic activity to the regions where they land. For example, according to a recent Analysys Mason study, Google’s historical and future network infrastructure investments in Japan are forecasted to enable an additional $303 billion (USD) in GDP cumulatively between 2022 and 2026.

The width of a garden hose, the Topaz cable will house 16 fiber pairs, for a total capacity of 240 Terabits per second (not to be confused with TSPs). It includes support for Wavelength Selective Switch (WSS), an efficient and software-defined way to carve up the spectrum on an optical fiber pair for flexibility in routing and advanced resilience. We’re proud to bring WSS to Topaz and to see the technology is being implemented widely across the submarine cable industry.

While Topaz is the first trans-Pacific fiber cable to land on the West Coast of Canada, it’s not the first communication cable to connect to Vancouver Island. In the 1960s, the Commonwealth Pacific Cable System (COMPAC) was a copper undersea cable linking Vancouver with Honolulu (United States), Sydney (Australia), and Auckland (New Zealand), expanding high-quality international phone connectivity. Today, COMPAC is no longer in service but its legacy lives on. The original cable landing station in Vancouver — the facility where COMPAC made landfall on Canadian soil — has been upgraded to fit the needs of modern fiber optics and will house the eastern end of the Topaz cable.

Traditional and treaty rights, and local communities, are deeply important to our infrastructure projects. The Topaz cable is built alongside the traditional territories of the Hupacasath, Maa-nulth, and Tseshaht, and we have consulted with and partnered with these First Nations every step of the way.

“Tseshaht is very proud of this collaboration and our partnership with Google, who has been very respectful and thoughtful in its engagement with our Nation. That’s how we carry ourselves and that’s how we want business to carry themselves in our territory.“ — Tseshaht First Nation – Elected Chief Councillor-Ken Watts

“The five First Nations of the Maa-nulth Treaty Society are pleased that we have concluded an agreement with Google Canada and have consented to the installation of a new, high-speed fiber optic cable through our traditional territories. This agreement, in which both Google Canada and our Nations benefit, is based on respect for our constitutionally protected treaty and aboriginal rights and enhances the process of reconciliation. We would also like to acknowledge the sensitivity that Google Canada expressed during our talks in regard to the pain and trauma experienced by our people as a result of residential school experience. We look forward to a long and mutually beneficial relationship with Google Canada.” —Chief Charlie Cootes, President of the Maa-nulth Treaty Society

“Google’s respect towards our Nation is appreciated and has good energy behind it.” —Hupacasath First Nation – Elected Chief Councilor – Brandy Lauder

With the addition of Topaz today, we have announced investments in 20 subsea cable projects. This includes Curie, Dunant, Equiano, Firmina and Grace Hopper, and consortium cables like Blue, Echo, Havfrue and Raman — all connecting 29 cloud regions, 88 zones, 146 network edge locations across more than 200 countries and territories. Learn about Google Cloud’s network and infrastructure on our website and in the below video.

VMs and their relevance to a cloud-native future: A conversation

Last week, we published the first episode of VM End-to-End, a series of curated conversations between a “VM skeptic” and a “VM enthusiast”. Join Brian and Carter as they explore why VMs are some of Google’s most trusted and reliable offerings, and how VMs benefit companies operating at scale in the cloud. Here’s a transcript of the first episode:

Carter Morgan (VM skeptic): My team asked me to research VMs and see how they compare to other cloud-native approaches, like microservices, containers, and serverless. And to be honest with you, I am not excited about it at all. So I’ve brought in someone who is, Brian, resident VM expert. Welcome, Brian!

Brian Dorsey (VM enthusiast): Hello. I’m super happy to be here, because I am really excited about VMs.

Carter: How? See this is why I wanted to bring you here. I don’t understand how you can be so excited about VMs, already?

Brian: How can you not? It is like the best of both worlds. You’ve got a stable, reliable system you can run anything on, and you’re in the cloud, close to all of the new features, and you get new automation tooling.

Carter: See, that’s what I’m kind of skeptical about. When I think about the features of a modern system, I’m not sure that a VM can provide me with those.

Brian: Okay. Well, let’s be kind of specific there. What do you mean by a modern system?

Carter: When I think about a modern system, I think about things like modularity. I think about scalability and reliability. I want automation. I don’t want to have to do everything manually. I even think about portability and being able to move my workloads wherever they need to go. I also don’t want to implement everything by hand. I don’t want to have to do everything myself. Is that something I can get with a VM?

Brian: Yeah. Great, because I actually think we can get most of that, and I wonder, why not? Let’s go one level deeper and then we’ll come back out. In your mind, what is a VM?

Carter: Oh, you’re putting me on the spot, Brian?!

Brian: Yep.

Carter: Okay. A VM, it’s a computer, but it’s a virtualization. It’s a slice of a computer. And so, what it lets you do is it lets you run multiple operating systems on one machine, so it looks like you have multiple machines running on one physical machine.

Brian: Yep. Absolutely. And in the cloud kind of not.

Carter: Oh, what?

Brian: Yeah. So here’s why I say not. The obstructions are all there, so you’ve got memory CPU, disk, networking. And instead of from one computer, in the cloud, that’s coming from all of the computers in a data center. So the CPU is coming from a lot of machines. The networking is from the whole data center. And so, I like to think about it as instead of a slice of a computer, it’s a slice of the data center

Carter: Instead of a slice of a computer, it’s a slice of a data center. That sounds interesting. Impressive, even. But also abstract. Do you have some examples of features that you can get from a cloud VM that you can’t get from a traditional VM on one machine?

Brian: My turn to be specific. Yeah. I think one example is like bin packing. You talk about these VMs, and their different shapes. So you have one that needs a lot of CPU and another that needs a lot of memory. Maybe you’ve got a bunch of them that need a lot of CPU and they don’t fit so well in the same box without orphaning some of the memory or CPU. And if you’re running those in a whole data center, or you can basically just leave it to Google to solve that problem, you can just have whatever shape machine you want and we’ll figure out where to put it. Basically, that lets you customize your machines to exactly what you need.

Carter: Okay. That’s very interesting, because that’s a hard problem. And so, if you can just let Google handle where your workloads are going to go, that’s a good benefit. If that’s the only benefit of cloud VMs though, I’m not sure I’m sold on them over other approaches. Is there anything else we got?

Brian: Absolutely. There’s a ton of stuff we could talk about in terms of automation and other things. But I think another really concrete example is disks, and it’s kind of my favorite there, because you think about a physical disk and you read and write blocks from it, right? It’s a block device. In the data center level, those blocks could be on hundreds or thousands of different machines, and so all of them are working together to give you more reliability and make things smoother, more predictable in terms of performance. So what you get out of it is something that looks a lot like a SAN, you can take backups of disks that are running even, or if you’ve run out of space, like I think almost all of us have, you can just make the disk bigger. So, things like that.

Carter: That’s impressive, especially like you’re saying being able to run and just scale up, scale down or resize. Okay. Then another very targeted question. It’s going to sound like a dig. I don’t mean it to you. Google’s putting a lot of effort and resources into Google Kubernetes Engine (GKE). And so, is Google even still investing in VMs?

Brian: Absolutely. Where do you think these containers run? Every Kubernetes cluster is running on top of a whole bunch of VMs. And so, everything you learned about VMs applies to those clusters that you’re running. Also, another example is our managed databases, so Cloud SQL. So if you’re running Postgres or MySQL on a Cloud SQL, that’s running on VMs. And there’s a bunch of other examples, too.

Carter: I can’t get away from VMs, even if I tried, it sounds like.

Brian: Nope.

Carter: Okay. The way you’re saying that is making me think that maybe I need to rethink my idea that VMs are just old, dusty pieces of technology. So I want to be clear, definitively, are you saying that VMs have a place in a cloud-native future?

Brian: Absolutely. I want to take old and dusty and turn that into mature and reliable. Then the future part, all these things are built on top of it and we’re building new things over time. So we’ve got tools for scaling clusters of machines up and down. That’s using Kubernetes, but you can use it directly. And we keep investing and doing more and more things there. So, absolutely, part of the future as well.

Carter: Okay. Then what about if I wanted to switch to them? I’m pretty familiar with Kubernetes. It’s fairly easy to get started. What about with VM? Is it going to take me years to get started on these?

Brian: No. It’s just a computer. Basically, anything that’s already running on a computer somewhere, even if you don’t have the team who built it nearby, you can run that on a VM and in turn you can run it on a cloud VM and get a bunch of the cloud benefits as well.

Carter: All right. I must admit that you’ve swayed me a little bit. I’m still skeptical, but what you said made a lot of sense. I still have a lot of questions. I want to know about keeping costs down. I want to know how to update VMs. I have this idea in my head that they’re really slow to start and stop. Stateful data, I’m curious about that.

Brian: Awesome. How much time do you have?

Carter: All right. You know what, let’s have this convo another day, and maybe, just maybe we can agree that VMs do matter in a cloud-native future.

Every year at CES, people from around the world experience the latest and greatest that consumer tech has to offer. In 2021, CES will be in an all-digital format for the first time.

So how can a virtual show like CES create immersive experiences for attendees tuning in remotely? That’s an interesting challenge for the cloud, and of course, every challenge presents an opportunity.

Google Cloud and 5G help enterprises deliver new experiences

Earlier in 2020, we announced our enterprise telecommunications strategy to deliver workloads to the network edge on Google Cloud, and during our SearchOn event last October, we announced how cloud streaming technology can power augmented reality (AR) in consumer search results.

Now, we’re merging the best of both worlds: Technology built for consumer search can take advantage of our enterprise edge capabilities. In light of the COVID-19 pandemic, this past year accelerated our support for enhanced consumer experiences across the board in novel ways. For example, we attempted to address questions such as how potential buyers can make a purchasing decision when they can’t see the product up close. This question becomes even more critical when considering a large purchase such as a new car.

That’s exactly what Fiat Chrysler Automobiles (FCA) and Google Cloud are working together to solve. As part of FCA’s Virtual Showroom CES event, you can experience the new innovative 2021 Jeep Wrangler 4xe by scanning a QR code with your phone. You can then see an Augmented Reality (AR) model of the Wrangler right in front of you—conveniently in your own driveway or in any open space. Check out what the car looks like from any angle, in different colors, and even step inside to see the interior with incredible details.

“As we continue our journey towards becoming a customer-centric mobility company, FCA is adopting emerging technologies that enable us to accelerate and deliver at the speed of our customers’ expectations,” said Mamatha Chamarthi, Chief Information Officer, FCA – North America and Asia Pacific. “Through our collaborative partnership with Google, we are able to expand our efforts to provide an immersive customer experience.”

Harnessing the power of edge with 5G

In order to create a mixed-reality experience with a 3D car model, computer-aided design (CAD)-based data sources that represent a 3D vehicle with highly detailed geometry, depth, texture, and lighting were used. High-fidelity models, such as cars with full interiors, often mean large files (GBs in size). Traditionally, depending on your connection, this can result in long waiting times as assets are downloaded onto your phone. In addition, while mobile phones are more powerful than the Apollo Guidance Computer, they are no match for the power we have in the cloud. We still want to bring these high end experiences to everyone, regardless of their respective device or geographical location.

We solve this problem by rendering the model in Google Cloud, then streaming it to the devices.

Specifically, the Cloud AR tech uses a combination of edge computing and AR technology to offload the computing power needed to display large 3D files, rendered by Unreal Engine, and stream them down to AR-enabled devices using Google’s Scene Viewer. Using powerful rendering servers with gaming console grade GPUs, memory, and processors located geographically near the user, we’re able to deliver a powerful but low friction, low latency experience. This rendering hardware allows us to load models with tens of millions of triangles and textures up to 4k, allowing the content we serve to be orders of magnitude larger than what’s served on mobile devices (i.e., on-device rendered assets). Doing so leverages high-speed 5G connectivity and streams directly from Google Cloud’s distributed edge, delivering a rich, photorealist immersive experience. Customers like FCA benefit from Google’s years of investment and expertise in streaming technology (have you tried playing Cyberpunk2077 on Stadia yet?). With the expansion of 5G networks, not only will streaming enable the experience for anyone anywhere, but it will also cut the wait time of downloading large assets required for detailed AR/VR experiences, ultimately providing instant gratification.

Applications and experiences are at the core of a winning edge proposition

We’re working to make these capabilities available to all enterprise customers to enable innovative use cases such as leveraging AR to help design teams collaborate, technicians perform machine diagnostics, creating next-generation, live video experiences for sports events, enabling new customer experiences across many industries, and supporting our customers in their digital transformation. Stay tuned!

To see the Jeep Wrangler 4xe come to life whether you’re attending CES or not, scan the QR code below, or check out the FCA CES website. Depending on your OS, device, and network strength, you will see either a photorealistic, cloud-streamed AR model or an on-device 3D car model, both of which can then be placed in your physical environment.