This topic describes the features of GPU-accelerated compute optimized instance families and lists the instance types of each family.

gn7, GPU-accelerated compute optimized instance family

This instance family is in invitational preview and unavailable for purchase.

Features
  • Compute:
    • Uses NVIDIA A100 GPUs. NVSwitches are used to establish connections between NVIDIA A100 GPUs. The GPUs have the following features:
      • Innovative Ampere architecture
      • 40 GB HBM2 memory per GPU
    • Uses 2.5 GHz Intel® Xeon® Platinum 8269CY (Cascade Lake) processors.
  • Storage:
    • Is an instance family in which all instances are I/O optimized.
    • Supports enhanced SSDs (ESSDs), standard SSDs, and ultra disks.
  • Network:
    • Supports IPv6.
    • Provides high network performance based on large computing capacity.
  • Suits the following scenarios:
    • Deep learning applications such as training applications of AI algorithms used in image classification, autonomous vehicles, and speech recognition
    • Scientific computing applications that have high GPU workloads such as computational fluid dynamics, computational finance, molecular dynamics, and environmental analysis
Instance types
Instance type vCPUs Memory (GiB) GPUs GPU memory Bandwidth (Gbit/s) Packet forwarding rate (Kpps) NIC queues ENIs
ecs.gn7-c12g1.3xlarge 12 95.0 NVIDIA A100 × 1 40 GB × 1 4.0 2,500 4 8
ecs.gn7-c13g1.13xlarge 52 380.0 NVIDIA A100 × 4 40 GB × 4 15.0 9,000 16 8
ecs.gn7-c13g1.26xlarge 104 760.0 NVIDIA A100 × 8 40 GB × 8 30.0 18,000 16 16
Note

vgn6i, lightweight GPU-accelerated compute optimized instance family

Features
  • If you want your vgn6i instance to support graphics features such as Open Graphics Library (OpenGL), you must purchase a GRID license from NVIDIA. Then, you must create an instance and manually install a GRID driver and activate the license after the instance is created.
  • Compute:
    • Uses NVIDIA T4 GPUs.
    • Is equipped with vGPUs that are generated from GPU virtualization with mediated pass-through.
      • Supports the 1/4 and 1/2 computing capacity of NVIDIA Tesla T4 GPUs.
      • Supports 4 GB and 8 GB of GPU video memory.
    • Offers a CPU-to-memory ratio of 1:5.
    • Uses 2.5 GHz Intel® Xeon® Platinum 8163 (Skylake) processors.
  • Storage:
    • Is an instance family in which all instances are I/O optimized.
    • Supports only standard SSDs and ultra disks.
  • Network:
    • Supports IPv6.
    • Provides high network performance based on large computing capacity.
  • Suits the following scenarios:
    • Real-time rendering for cloud games
    • Real-time rendering for AR and VR applications
    • AI (deep learning and machine learning) inference for elastic Internet service deployment
    • Educational environment of deep learning
    • Modeling experiment environment of deep learning
Instance types
Instance type vCPUs Memory (GiB) GPUs GPU memory Bandwidth (Gbit/s) Packet forwarding rate (Kpps) NIC queues ENIs Private IP addresses per ENI
ecs.vgn6i-m4.xlarge 4 23.0 NVIDIA T4 × 1/4 16 GB × 1/4 3.0 500 2 4 10
ecs.vgn6i-m8.2xlarge 10 46.0 NVIDIA T4 × 1/2 16GB × 1/2 4.0 800 4 5 20
Note

gn6i, GPU-accelerated compute optimized instance family

Features
  • Compute:
    • Uses NVIDIA T4 GPUs that have the following features:
      • Innovative NVIDIA Turing architecture
      • 16 GB memory per GPU (320 GB/s bandwidth)
      • 2,560 CUDA cores per GPU
      • Up to 320 Turing Tensor cores per GPU
      • Mixed-precision Tensor cores that support 65 FP16 TFLOPS, 130 INT8 TOPS, and 260 INT4 TOPS
    • Offers a CPU-to-memory ratio of 1:4.
    • Uses 2.5 GHz Intel® Xeon® Platinum 8163 (Skylake) processors.
  • Storage:
    • Is an instance family in which all instances are I/O optimized.
    • Supports standard SSDs, ultra disks, and ESSDs that deliver millions of IOPS.
  • Network:
    • Supports IPv6.
    • Provides high network performance based on large computing capacity.
  • Suits the following scenarios:
    • AI (deep learning and machine learning) inference for computer vision, speech recognition, speech synthesis, natural language processing (NLP), machine translation, and recommendation systems
    • Real-time rendering for cloud games
    • Real-time rendering for AR and VR applications
    • Graphics workstations or overloaded graphics computing
    • GPU-accelerated databases
    • High-performance computing
Instance types
Instance type vCPUs Memory (GiB) GPUs GPU memory Bandwidth (Gbit/s) Packet forwarding rate (Kpps) Baseline storage IOPS NIC queues ENIs Private IP addresses per ENI
ecs.gn6i-c4g1.xlarge 4 15.0 NVIDIA T4 × 1 16 GB × 1 4.0 500 None 2 2 10
ecs.gn6i-c8g1.2xlarge 8 31.0 NVIDIA T4 × 1 16 GB × 1 5.0 800 None 2 2 10
ecs.gn6i-c16g1.4xlarge 16 62.0 NVIDIA T4 × 1 16 GB × 1 6.0 1,000 None 4 3 10
ecs.gn6i-c24g1.6xlarge 24 93.0 NVIDIA T4 × 1 16 GB × 1 7.5 1,200 None 6 4 10
ecs.gn6i-c24g1.12xlarge 48 186.0 NVIDIA T4 × 2 16 GB × 2 15.0 2,400 None 12 6 10
ecs.gn6i-c24g1.24xlarge 96 372.0 NVIDIA T4 × 4 16 GB × 4 30.0 4,800 250,000 24 8 10
Note

gn6e, GPU-accelerated compute optimized instance family

Features
  • Compute:
    • Uses NVIDIA V100 GPUs that each have 32 GB of GPU memory and support NVLink.
    • Uses NVIDIA V100 GPUs (SXM2-based) that have the following features:
      • Innovative Volta architecture
      • 32 GB HBM2 memory per GPU (900 GB/s bandwidth)
      • 5,120 CUDA cores per GPU
      • 640 Tensor cores per GPU
      • Up to six NVLink links and a total bandwidth of 300 GB/s (25 GB/s per NVlink link per direction)
    • Offers a CPU-to-memory ratio of 1:8.
    • Uses 2.5 GHz Intel® Xeon® Platinum 8163 (Skylake) processors.
  • Storage:
    • Is an instance family in which all instances are I/O optimized.
    • Supports ESSDs, standard SSDs, and ultra disks.
  • Network:
    • Supports IPv6.
    • Provides high network performance based on large computing capacity.
  • Suits the following scenarios:
    • Deep learning applications such as training and inference applications of AI algorithms used in image classification, autonomous vehicles, and speech recognition
    • Scientific computing applications such as fluid dynamics, finance, molecular dynamics, and environmental analysis
Instance types
Instance type vCPUs Memory (GiB) GPUs GPU memory Bandwidth (Gbit/s) Packet forwarding rate (Kpps) NIC queues ENIs Private IP addresses per ENI
ecs.gn6e-c12g1.3xlarge 12 92.0 NVIDIA V100 × 1 32 GB× 1 5.0 800 8 6 10
ecs.gn6e-c12g1.12xlarge 48 368.0 NVIDIA V100 × 4 32 GB × 4 16.0 2,400 8 8 20
ecs.gn6e-c12g1.24xlarge 96 736.0 NVIDIA V100 × 8 32 GB × 8 32.0 4,800 16 8 20
Note

gn6v, GPU-accelerated compute optimized instance family

Features
  • Compute:
    • Uses NVIDIA V100 GPUs.
    • Uses NVIDIA V100 GPUs (SXM2-based) that have the following features:
      • Innovative Volta architecture
      • 16 GB HBM2 memory per GPU (900 GB/s bandwidth)
      • 5,120 CUDA cores per GPU
      • 640 Tensor cores per GPU
      • Up to six NVLink links and a total bandwidth of 300 GB/s (25 GB/s per NVlink link per direction)
    • Offers a CPU-to-memory ratio of 1:4.
    • Uses 2.5 GHz Intel® Xeon® Platinum 8163 (Skylake) processors.
  • Storage:
    • Is an instance family in which all instances are I/O optimized.
    • Supports ESSDs, standard SSDs, and ultra disks.
  • Network:
    • Supports IPv6.
    • Provides high network performance based on large computing capacity.
  • Suits the following scenarios:
    • Deep learning applications such as training and inference applications of AI algorithms used in image classification, autonomous vehicles, and speech recognition
    • Scientific computing applications such as fluid dynamics, finance, molecular dynamics, and environmental analysis
Instance types
Instance type vCPUs Memory (GiB) GPUs GPU memory Bandwidth (Gbit/s) Packet forwarding rate (Kpps) Baseline storage IOPS NIC queues ENIs Private IP addresses per ENI
ecs.gn6v-c8g1.2xlarge 8 32.0 NVIDIA V100 × 1 16 GB × 1 2.5 800 None 4 4 10
ecs.gn6v-c8g1.8xlarge 32 128.0 NVIDIA V100 × 4 16 GB × 4 10.0 2,000 None 8 8 20
ecs.gn6v-c8g1.16xlarge 64 256.0 NVIDIA V100 × 8 16 GB × 8 20.0 2,500 None 16 8 20
ecs.gn6v-c10g1.20xlarge 82 336.0 NVIDIA V100 × 8 16 GB × 8 32.0 4,500 250,000 16 8 20
Note

vgn5i, lightweight GPU-accelerated compute optimized instance family

Features
  • If you want your vgn5i instance to support graphics features such as Open Graphics Library (OpenGL), you must purchase a GRID license from NVIDIA. Then, you must create an instance, and manually install a GRID driver and activate the license after the instance is created.
  • Compute:
    • Uses NVIDIA P4 GPUs.
    • Is equipped with vGPUs that are generated from GPU virtualization with mediated pass-through.
      • Supports the 1/8, 1/4, 1/2, and 1/1 computing capacity of NVIDIA Tesla P4 GPUs.
      • Supports 1 GB, 2 GB, 4 GB, and 8 GB of GPU memory.
    • Offers a CPU-to-memory ratio of 1:3.
    • Uses 2.5 GHz Intel® Xeon® E5-2682 v4 (Broadwell) processors.
  • Storage:
    • Is an instance family in which all instances are I/O optimized.
    • Supports only standard SSDs and ultra disks.
  • Network:
    • Supports IPv6.
    • Provides high network performance based on large computing capacity.
  • Suits the following scenarios:
    • Real-time rendering for cloud games
    • Real-time rendering for AR and VR applications
    • AI (deep learning and machine learning) inference for elastic Internet service deployment
    • Educational environment of deep learning
    • Modeling experiment environment of deep learning
Instance types
Instance type vCPUs Memory (GiB) GPUs GPU memory Bandwidth (Gbit/s) Packet forwarding rate (Kpps) NIC queues ENIs Private IP addresses per ENI
ecs.vgn5i-m1.large 2 6.0 NVIDIA P4 × 1/8 8 GB × 1/8 1.0 300 2 2 6
ecs.vgn5i-m2.xlarge 4 12.0 NVIDIA P4 × 1/4 8 GB × 1/4 2.0 500 2 3 10
ecs.vgn5i-m4.2xlarge 8 24.0 NVIDIA P4 × 1/2 8 GB × 1/2 3.0 800 2 4 10
ecs.vgn5i-m8.4xlarge 16 48.0 NVIDIA P4 × 1 8 GB × 1 5.0 1,000 4 5 20
Note

gn5, GPU-accelerated compute optimized instance family

Features
  • Compute:
    • Uses NVIDIA P100 GPUs.
    • Offers multiple CPU-to-memory ratios.
    • Uses 2.5 GHz Intel® Xeon® E5-2682 v4 (Broadwell) processors.
  • Storage:
    • Supports high-performance local NVMe SSDs.
    • Is an instance family in which all instances are I/O optimized.
    • Supports only standard SSDs and ultra disks.
  • Network:
    • Provides high network performance based on large computing capacity.
  • Suits the following scenarios:
    • Deep learning
    • Scientific computing applications, such as fluid dynamics, finance, genomics, and environmental analysis
    • Server-side GPU compute workloads such as high-performance computing, rendering, and multi-media encoding and decoding
Instance types
Instance type vCPUs Memory (GiB) Local storage (GiB) GPUs GPU memory Bandwidth (Gbit/s) Packet forwarding rate (Kpps) NIC queues ENIs Private IP addresses per ENI
ecs.gn5-c4g1.xlarge 4 30.0 440 NVIDIA P100 × 1 16 GB × 1 3.0 300 1 3 10
ecs.gn5-c8g1.2xlarge 8 60.0 440 NVIDIA P100 × 1 16 GB × 1 3.0 400 1 4 10
ecs.gn5-c4g1.2xlarge 8 60.0 880 NVIDIA P100 × 2 16 GB × 2 5.0 1,000 2 4 10
ecs.gn5-c8g1.4xlarge 16 120.0 880 NVIDIA P100 × 2 16 GB × 2 5.0 1,000 4 8 20
ecs.gn5-c28g1.7xlarge 28 112.0 440 NVIDIA P100 × 1 16 GB × 1 5.0 1,000 8 8 20
ecs.gn5-c8g1.8xlarge 32 240.0 1,760 NVIDIA P100 × 4 16 GB × 4 10.0 2,000 8 8 20
ecs.gn5-c28g1.14xlarge 56 224.0 880 NVIDIA P100 × 2 16 GB × 2 10.0 2,000 14 8 20
ecs.gn5-c8g1.14xlarge 54 480.0 3,520 NVIDIA P100 × 8 16 GB × 8 25.0 4,000 14 8 20
Note

gn5i, GPU-accelerated compute optimized instance family

Features
  • Compute:
    • Uses NVIDIA P4 GPUs.
    • Offers a CPU-to-memory ratio of 1:4.
    • Uses 2.5 GHz Intel® Xeon® E5-2682 v4 (Broadwell) processors.
  • Storage:
    • Is an instance family in which all instances are I/O optimized.
    • Supports only standard SSDs and ultra disks.
  • Network:
    • Supports IPv6.
    • Provides high network performance based on large computing capacity.
  • Suits the following scenarios:
    • Deep learning inference
    • Server-side GPU compute workloads such as multi-media encoding and decoding
Instance types
Instance type vCPUs Memory (GiB) GPUs GPU memory Bandwidth (Gbit/s) Packet forwarding rate (Kpps) NIC queues ENIs Private IP addresses per ENI
ecs.gn5i-c2g1.large 2 8.0 NVIDIA P4 × 1 8 GB × 1 1.0 100 2 2 6
ecs.gn5i-c4g1.xlarge 4 16.0 NVIDIA P4 × 1 8 GB × 1 1.5 200 2 3 10
ecs.gn5i-c8g1.2xlarge 8 32.0 NVIDIA P4 × 1 8 GB × 1 2.0 400 4 4 10
ecs.gn5i-c16g1.4xlarge 16 64.0 NVIDIA P4 × 1 8 GB × 1 3.0 800 4 8 20
ecs.gn5i-c16g1.8xlarge 32 128.0 NVIDIA P4 × 2 8 GB × 2 6.0 1,200 8 8 20
ecs.gn5i-c28g1.14xlarge 56 224.0 NVIDIA P4 × 2 8 GB × 2 10.0 2,000 14 8 20
Note