Why Amazon EC2 G4 Instances?
Amazon EC2 G4 instances are the industry’s most cost-effective and versatile GPU instances for deploying machine learning models such as image classification, object detection, and speech recognition, and for graphics-intensive applications such as remote graphics workstations, game streaming, and graphics rendering. G4 instances are available with a choice of NVIDIA GPUs (G4dn) or AMD GPUs (G4ad).
G4dn instances feature NVIDIA T4 GPUs and custom Intel Cascade Lake CPUs, and are optimized for machine learning inference and small scale training. These instances also bring high performance to graphics-intensive applications including remote workstations, game streaming, and graphics rendering. These instances are also ideal for customers who prefer to use NVIDIA software such as RTX Virtual Workstation and libraries such as CUDA, CuDNN, and NVENC.
G4ad instances feature the latest AMD Radeon Pro V520 GPUs and 2nd generation AMD EPYC processors. These instances provide the best price performance in the cloud for graphics applications including remote workstations, game streaming, and graphics rendering. Compared to comparable instances they offer up to 45% better price performance for graphics-intensive applications.
New Amazon EC2 G4ad Instances
Amazon EC2 G4dn Instances
G4dn instances, powered by NVIDIA T4 GPUs, are the lowest cost GPU-based instances in the cloud for machine learning inference and small scale training. They also provide high performance and are a cost-effective solution for graphics applications that are optimized for NVIDIA GPUs using NVIDIA libraries such as CUDA, CuDNN, and NVENC. They provide up to 8 NVIDIA T4 GPUs, 96 vCPUs, 100 Gbps networking, and 1.8 TB local NVMe-based SSD storage and are also available as bare metal instances.
G4dn Benefits
G4dn Features
Amazon EC2 G4ad Instances
G4ad instances, powered by AMD Radeon Pro V520 GPUs, provide the best price performance for graphics intensive applications in the cloud. These instances offer up to 45% better price performance compared to G4dn instances, which were already the lowest cost instances in the cloud, for graphics applications such as remote graphics workstations, game streaming, and rendering that leverage industry-standard APIs such as OpenGL, DirectX, and Vulkan. They provide up to 4 AMD Radeon Pro V520 GPUs, 64 vCPUs, 25 Gbps networking, and 2.4 TB local NVMe-based SSD storage.
G4ad Benefits
G4ad Features
Customer and Partner testimonials
Here are some examples of how customers and partners have achieved their business goals with Amazon EC2 G4 instances.
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Ubitus
Ubitus is an innovative company leading the way in building cloud gaming technology. Through their platforms, users can enjoy a AAA gaming experience on any device including smartphones, tablets, gaming consoles, smart TVs, and computers as long as they’re connected to a broadband network.
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Land F/X
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Duolingo
Duolingo is a free language education platform that has become the most popular way to learn languages online. Duolingo’s language learning scientists, machine learning engineers, and AI experts use data from over 300 million learners to constantly increase effectiveness of the platform.
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Blacknut
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Snap
In 2018, Snap Inc. (Snap), known for its Snapchat messaging app, had an intriguing new idea: create a series of animated videos starring each user’s Bitmoji, the personalized cartoon avatar that is Snapchat’s signature feature. Each week, Bitmoji TV would debut new episodes consisting of silly, professionally scripted and animated 3- to 8-minute videos in which Bitmojis of users and their friends were the stars, doing everything from fighting off zombies to competing in a low-gravity “Moonlympics.” With Amazon EC2 G4 Instances, Snap was able to create a fun, bold kind of personalized entertainment that rendered quickly enough for millions to enjoy simultaneously while keeping compute costs down.
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Nearmap
Nearmap was founded in Perth, Australia, in 2007 and has grown from a small startup to a leader in digital imaging. The company specializes in creating 2D and 3D images from aerial photos of landscapes, a valuable resource for a wide variety of industries. For Nearmap, the impact of upgrading to Amazon EC2 G4 instances was immediate and profound: the company was able to run three times as much data for the same cost as on Amazon EC2 G2 instances, in a process that felt effortless and whose integration felt seamless with the AWS tools it was already using.
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Untold Studios
Untold Studios deployed various AWS virtual workstation configurations, including G4 instances, which feature NVIDIA T4 GPUs and RTX technology, and are optimized for VFX and animation workflows. With expanded instance options to select from, Untold Studios can more accurately match virtual machine types to specific workloads, an approach that is beneficial both creatively and economically.
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Hive VFX
The workstations were first deployed with Amazon Elastic Compute Cloud (Amazon EC2) G3 Instances. But when Amazon EC2 G4 Instances—powered by NVIDIA T4 Tensor Core GPUs (NVIDIA’s latest generation of GPUs) and NVIDIA RTX technology, the latest technology for high-performance simulation, rendering, and design—became available, Hive VFX was able to upgrade easily and quickly.
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Humen
The Doritos’ Super Bowl 2020 commercial showcased a dance off between 75-year-old actor Sam Elliott and 21-year-old rapper Lil Nas X, a competition made possible using artificial intelligence technology developed by a startup called Humen, the parent company behind Sway. This tiny company was able to earn a partnership with megacompany Doritos for a Super Bowl campaign and launch Sway, an app that topped the charts in the App Store, with the help of Amazon Web Services (AWS). To take on the colossal workload of launching a graphics-intensive application during the Super Bowl, Humen used Amazon Elastic Compute Cloud (Amazon EC2) G4 Instances—and achieved super results.
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The Molecule
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PureWeb
Product Details
Instance Size | GPU | vCPUs | Memory (GiB) | Instance Storage (GB) | Network Bandwidth (Gbps) | EBS Bandwidth (Gbps) | On-Demand Price/hr* | 1-yr Reserved Instance Effective Hourly* (Linux) | 3-yr Reserved Instance Effective Hourly* (Linux) | |
G4dn |
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Single GPU VMs | g4dn.xlarge | 1 | 4 | 16 | 1 x 125 NVMe SSD | Up to 25 | Up to 3.5 | $0.526 | $0.316 | $0.210 |
g4dn.2xlarge | 1 | 8 | 32 | 1 x 225 NVMe SSD | Up to 25 | Up to 3.5 | $0.752 | $0.452 | $0.300 | |
g4dn.4xlarge | 1 | 16 | 64 | 1 x 225 NVMe SSD | Up to 25 | 4.75 | $1.204 | $0.722 | $0.482 | |
g4dn.8xlarge | 1 | 32 | 128 | 1 x 900 NVMe SSD | 50 | 9.5 | $2.176 | $1.306 | $0.870 | |
g4dn.16xlarge | 1 | 64 | 256 | 1 x 900 NVMe SSD | 50 | 9.5 | $4.352 | $2.612 | $1.740 | |
Multi GPU VMs | g4dn.12xlarge | 4 | 48 | 192 | 1 x 900 NVMe SSD | 50 | 9.5 | $3.912 | $2.348 | $1.564 |
g4dn.metal | 8 | 96 | 384 | 2 x 900 NVMe SSD | 100 | 19 | $7.824 | $4.694 | $3.130 | |
G4ad |
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Single GPU VMs | g4ad.xlarge | 1 | 4 | 16 | 1 x 150 NVMe SSD | Up to 10 | Up to 3 | $0.379 | $0.227 | $0.178 |
g4ad.2xlarge | 1 | 8 | 32 | 1 x 300 NVMe SSD | Up to 10 | Up to 3 | $0.541 | $0.325 | $0.254 | |
g4ad.4xlarge | 1 | 16 | 64 | 1 x 600 NVMe SSD | Up to 10 | Up to 3 | $0.867 | $0.520 | $0.405 | |
Multi GPU VMs | g4ad.8xlarge | 2 | 32 | 128 | 1 x 1200 NVMe SSD | 15 | 3 | $1.734 | $1.040 | $0.810 |
g4ad.16xlarge | 4 | 64 | 256 | 1 x 2400 NVMe SSD | 25 | 6 | $3.468 | $2.081 | $1.619 |
* Prices shown are for US East (Northern Virginia) AWS Region. Prices for 1-year and 3-year reserved instances are for "Partial Upfront" payment options or "No Upfront" for instances without the Partial Upfront option.
Get Started with G4dn Instances
Using pre-built AMIs and containers from AWS
Using Amazon Deep Learning AMIs or Deep Learning Containers, you can quickly launch Amazon EC2 instances pre-installed with popular deep learning frameworks and interfaces such as TensorFlow, PyTorch, and MXNet to train sophisticated, custom AI models, experiment with new algorithms, or to learn new skills and techniques. To learn more, visit the Amazon Deep Learning AMIs product page or the AWS Deep Learning Containers product page.
NVIDIA RTX Virtual Workstation AMIs support running up to four 4K displays per GPU for visualization apps. NVIDIA Gaming AMIs render videos at 60 FPS and support running a single 4K display on a per GPU basis.
Building your own custom AMI with NVIDIA drivers
The NVIDIA Data Center drivers provide the best performance for highly intensive computational workloads often found in Deep Learning, Data Science, and HPC.
NVIDIA RTX drivers can be used to enable NVIDIA RTX Virtual Workstation software. RTX vWS offers support for up to four 4K displays on a per GPU basis. NVIDIA Gaming drivers support the world's most advanced graphics cards, gaming solutions, and gaming technology. This driver offers support for a single 4K display on a per GPU basis.
To learn how to install these drivers onto your instance, follow these links for Linux and Windows.
Get Started with G4ad Instances
Using pre-built AMIs from AWS
AMD Radeon Pro Software for Enterprise drivers provide high performance graphics for virtual workstations, game streaming, rendering, and other graphics applications. To get started quickly, you can use AWS provided AMIs that include AMD Radeon Pro Software for Enterprise pre-installed. These AMIs are available on the AMD Radeon Pro Marketplace.
Building your own custom AMI with AMD drivers
AMD Radeon Pro Software for Enterprise drivers can be used to configure instances with powerful and reliable professional-grade graphics. Workstations provisioned with these drivers can support up to two 4K displays.
To learn how to install these drivers on your instance to build your own custom AMI, follow these links for Linux and Windows.