This topic describes the features of GPU-accelerated compute-optimized and vGPU-accelerated instance families of Elastic Compute Service (ECS) and lists the instance types of each instance family.

sgn7i-vws, vGPU-accelerated instance family with shared CPUs

Features:
  • This instance family uses third-generation SHENLONG architecture to provide predictable and consistent ultra-high performance. This instance family utilizes fast path acceleration on the chip to improve storage performance, network performance, and computing stability by an order of magnitude. This way, data can be stored and models can be loaded more quickly.
  • Instances of the sgn7i-vws instance family share CPU and network resources to maximize the utilization of underlying resources. Each instance has exclusive access to its memory and GPU memory to ensure data isolation and high performance.
    Note If you want to use exclusive CPU resources, select the vgn7i-vws instance family.
  • This instance family comes with the NVIDIA GRID vWS license to provide certified graphics acceleration capabilities for Computer Aided Design (CAD) software to meet the requirements of professional graphic design. Instances of this instance family can be used as lightweight GPU-accelerated compute-optimized instances to reduce the costs of small-scale AI inference tasks.
  • Compute:
    • Uses NVIDIA A10 GPUs that have the following features:
      • Innovative Ampere architecture
      • Support for acceleration features such as vGPU, RTX, and the TensorRT inference engine that provide all-purpose business support
    • Uses 2.9 GHz Intel® Xeon® Scalable (Ice Lake) processors that deliver an all-core turbo frequency of 3.5 GHz.
  • Storage:
    • Is an instance family in which all instances are I/O optimized.
    • Supports enhanced SSDs (ESSDs), standard SSDs, and ultra disks.
      Note For more information about the performance of cloud disks, see EBS performance.
  • Network:
    • Supports IPv6 addresses.
    • Provides high network performance based on large computing capacity.
  • Applicable scenarios:
    • Concurrent AI inference tasks that require high-performance CPUs, memory, and GPUs, such as image recognition, speech recognition, and behavior identification
    • Compute-intensive graphics processing tasks that require high-performance 3D graphics virtualization capabilities, such as remote graphic design and cloud gaming
    • 3D modeling in fields that require the use of Ice Lake processors, such as animation and film production, cloud gaming, and mechanical design
Instance types
Instance type vCPU Memory (GiB) GPU GPU memory Baseline/Burst bandwidth (Gbit/s) Packet forwarding rate (pps) NIC queues ENIs
ecs.sgn7i-vws-m2.xlarge 4 15.5 NVIDIA A10 * 1/12 24GB * 1/12 1.5/5 500,000 4 2
ecs.sgn7i-vws-m4.2xlarge 8 31 NVIDIA A10 * 1/6 24GB * 1/6 2.5/10 1,000,000 4 4
ecs.sgn7i-vws-m8.4xlarge 16 62 NVIDIA A10 * 1/3 24GB * 1/3 5/20 2,000,000 8 4
ecs.sgn7i-vws-m2s.xlarge 4 8 NVIDIA A10 * 1/12 24GB * 1/12 1.5/5 500,000 4 2
ecs.sgn7i-vws-m4s.2xlarge 8 16 NVIDIA A10 * 1/6 24GB * 1/6 2.5/10 1,000,000 4 4
ecs.sgn7i-vws-m8s.4xlarge 16 32 NVIDIA A10 * 1/3 24GB * 1/3 5/20 2,000,000 8 4
Note

vgn7i-vws, vGPU-accelerated instance family

Features:
  • This instance family uses third-generation SHENLONG architecture to provide predictable and consistent ultra-high performance. This instance family utilizes fast path acceleration on the chip to improve storage performance, network performance, and computing stability by an order of magnitude. This way, data can be stored and models can be loaded more quickly.
  • This instance family comes with the NVIDIA GRID vWS license to provide certified graphics acceleration capabilities for CAD software to meet the requirements of professional graphic design. Instances of this instance family can also be used as lightweight GPU-accelerated compute-optimized instances to reduce the costs of small-scale AI inference tasks.
  • Compute:
    • Uses NVIDIA A10 GPUs that have the following features:
      • Innovative Ampere architecture
      • Support for acceleration features such as vGPU, RTX, and the TensorRT inference engine that provide all-purpose business support
    • Uses 2.9 GHz Intel® Xeon ® Scalable (Ice Lake) processors that deliver an all-core turbo frequency of 3.5 GHz.
  • Storage:
    • Is an instance family in which all instances are I/O optimized.
    • Supports ESSDs, standard SSDs, and ultra disks.
      Note For more information about the performance of cloud disks, see EBS performance.
  • Network:
    • Supports IPv6 addresses.
    • Provides high network performance based on large computing capacity.
  • Applicable scenarios:
    • Concurrent AI inference tasks that require high-performance CPUs, memory, and GPUs, such as image recognition, speech recognition, and behavior identification
    • Compute-intensive graphics processing tasks that require high-performance 3D graphics virtualization capabilities, such as remote graphic design and cloud gaming
    • 3D modeling in fields that require the use of Ice Lake processors, such as animation and film production, cloud gaming, and mechanical design
Instance types
Instance type vCPU Memory (GiB) GPU GPU memory Bandwidth (Gbit/s) Packet forwarding rate (pps) NIC queues ENIs
ecs.vgn7i-vws-m4.xlarge 4 30 NVIDIA A10 * 1/6 24GB * 1/6 3 1,000,000 4 4
ecs.vgn7i-vws-m8.2xlarge 10 62 NVIDIA A10 * 1/3 24GB * 1/3 5 2,000,000 8 6
ecs.vgn7i-vws-m12.3xlarge 14 93 NVIDIA A10 * 1/2 24GB * 1/2 8 3,000,000 8 6
ecs.vgn7i-vws-m24.7xlarge 30 186 NVIDIA A10 * 1 24GB * 1 16 6,000,000 12 8
Note

gn7i, GPU-accelerated compute-optimized instance family

Features:
  • This instance family uses third-generation SHENLONG architecture to provide predictable and consistent ultra-high performance. This instance family utilizes fast path acceleration on the chip to improve storage performance, network performance, and computing stability by an order of magnitude.
  • Compute:
    • Uses NVIDIA A10 GPUs that have the following features:
      • Innovative Ampere architecture
      • Support for acceleration features such as RTX and the TensorRT inference engine
    • Uses 2.9 GHz Intel® Xeon® Scalable (Ice Lake) processors that deliver an all-core turbo frequency of 3.5 GHz.
    • Provides a maximum memory of 752 GiB, which is much larger than the memory sizes of the gn6i instance family.
  • Storage:
    • Is an instance family in which all instances are I/O-optimized.
    • Supports ESSDs, standard SSDs, and ultra disks.
  • Network:
    • Supports IPv6 addresses.
    • Provides high network performance based on large computing capacity.
  • Applicable scenarios:
    • Concurrent AI inference tasks that require high-performance CPUs, memory, and GPUs, such as image recognition, speech recognition, and behavior identification
    • Compute-intensive graphics processing tasks that require high-performance 3D graphics virtualization capabilities, such as remote graphic design and cloud gaming
Instance types
Instance type vCPU Memory (GiB) GPU GPU memory Bandwidth (Gbit/s) Packet forwarding rate (pps) NIC queues ENIs
ecs.gn7i-c8g1.2xlarge 8 30 NVIDIA A10 * 1 24GB * 1 16 1,600,000 8 4
ecs.gn7i-c16g1.4xlarge 16 60 NVIDIA A10 * 1 24GB * 1 16 3,000,000 8 8
ecs.gn7i-c32g1.8xlarge 32 188 NVIDIA A10 * 1 24GB * 1 16 6,000,000 12 8
ecs.gn7i-c32g1.16xlarge 64 376 NVIDIA A10 * 2 24GB * 2 32 12,000,000 16 15
ecs.gn7i-c32g1.32xlarge 128 752 NVIDIA A10 * 4 24GB * 4 64 24,000,000 32 15
Note

gn7, GPU-accelerated compute-optimized instance family

Features:
  • Compute:
    • Uses NVIDIA A100 GPUs. NVSwitches are used to establish pairwise 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 ESSDs, standard SSDs, and ultra disks.
  • Network:
    • Supports IPv6 addresses.
    • Provides high network performance based on large computing capacity.
  • Applicable scenarios:
    • Deep learning applications such as the training applications of AI algorithms used in image classification, autonomous driving, and speech recognition
    • Scientific computing applications that require robust GPU computing capabilities such as computational fluid dynamics, computational finance, molecular dynamics, and environmental analysis
Instance types
Instance type vCPU Memory (GiB) GPU GPU memory Bandwidth (Gbit/s) Packet forwarding rate (pps) NIC queues ENIs
ecs.gn7-c12g1.3xlarge 12 95 NVIDIA A100 * 1 40GB * 1 4 2,500,000 4 8
ecs.gn7-c13g1.13xlarge 52 380 NVIDIA A100 * 4 40GB * 4 15 9,000,000 16 8
ecs.gn7-c13g1.26xlarge 104 760 NVIDIA A100 * 8 40GB * 8 30 18,000,000 16 16
Note

vgn6i, vGPU-accelerated 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, after the instance is created, you must manually install a GRID driver and activate the license.
  • Compute:
    • Uses NVIDIA T4 GPUs.
    • Uses vGPUs.
      • Supports the 1/4 and 1/2 compute capacity of NVIDIA Tesla T4 GPUs.
      • Supports 4 GB and 8 GB of GPU 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 addresses.
    • Provides high network performance based on large computing capacity.
  • Applicable scenarios:
    • Real-time rendering for cloud games
    • Real-time rendering for augmented reality (AR) and virtual reality (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 vCPU Memory (GiB) GPU GPU memory Bandwidth (Gbit/s) Packet forwarding rate (pps) NIC queues ENIs Private IP addresses per ENI
ecs.vgn6i-m4.xlarge 4 23 NVIDIA T4 * 1/4 16GB * 1/4 3 500,000 2 4 10
ecs.vgn6i-m8.2xlarge 10 46 NVIDIA T4 * 1/2 16GB * 1/2 4 800,000 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 (320 GB/s bandwidth) per GPU
      • 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 addresses.
    • Provides high network performance based on large computing capacity.
  • Applicable 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 computing that requires heavy workload
    • GPU-accelerated databases
    • High-performance computing
Instance types
Instance type vCPU Memory (GiB) GPU GPU memory Bandwidth (Gbit/s) Packet forwarding rate (pps) Baseline storage IOPS NIC queues ENIs Private IP addresses per ENI
ecs.gn6i-c4g1.xlarge 4 15 NVIDIA T4 * 1 16GB * 1 4 500,000 None 2 2 10
ecs.gn6i-c8g1.2xlarge 8 31 NVIDIA T4 * 1 16GB * 1 5 800,000 None 2 2 10
ecs.gn6i-c16g1.4xlarge 16 62 NVIDIA T4 * 1 16GB * 1 6 1,000,000 None 4 3 10
ecs.gn6i-c24g1.6xlarge 24 93 NVIDIA T4 * 1 16GB * 1 7.5 1,200,000 None 6 4 10
ecs.gn6i-c40g1.10xlarge 40 155 NVIDIA T4 * 1 16GB * 1 10 1,600,000 None 16 10 10
ecs.gn6i-c24g1.12xlarge 48 186 NVIDIA T4 * 2 16GB * 2 15 2,400,000 None 12 6 10
ecs.gn6i-c24g1.24xlarge 96 372 NVIDIA T4 * 4 16GB * 4 30 4,800,000 250,000 24 8 10
Note

gn6e, GPU-accelerated compute-optimized instance family

Features:
  • Compute:
    • Uses NVIDIA V100 GPUs that each has 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 (900 GB/s bandwidth) per GPU
      • Up to 5,120 CUDA cores per GPU
      • Up to 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 addresses.
    • Provides high network performance based on large computing capacity.
  • Applicable scenarios:
    • Deep learning applications such as the training and inference applications of AI algorithms used in image classification, autonomous driving, and speech recognition
    • Scientific computing applications such as computational fluid dynamics, computational finance, molecular dynamics, and environmental analysis
Instance types
Instance type vCPU Memory (GiB) GPU GPU memory Bandwidth (Gbit/s) Packet forwarding rate (pps) NIC queues ENIs Private IP addresses per ENI
ecs.gn6e-c12g1.3xlarge 12 92 NVIDIA V100 * 1 32GB * 1 5 800,000 8 6 10
ecs.gn6e-c12g1.12xlarge 48 368 NVIDIA V100 * 4 32GB * 4 16 2,400,000 8 8 20
ecs.gn6e-c12g1.24xlarge 96 736 NVIDIA V100 * 8 32GB * 8 32 4,800,000 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 (900 GB/s bandwidth) per GPU
      • Up to 5,120 CUDA cores per GPU
      • Up to 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 addresses.
    • Provides high network performance based on large computing capacity.
  • Applicable scenarios:
    • Deep learning applications such as the training and inference applications of AI algorithms used in image classification, autonomous driving, and speech recognition
    • Scientific computing applications such as computational fluid dynamics, computational finance, molecular dynamics, and environmental analysis
Instance types
Instance type vCPU Memory (GiB) GPU GPU memory Bandwidth (Gbit/s) Packet forwarding rate (pps) Baseline storage IOPS NIC queues ENIs Private IP addresses per ENI
ecs.gn6v-c8g1.2xlarge 8 32 NVIDIA V100 * 1 16GB * 1 2.5 800,000 None 4 4 10
ecs.gn6v-c8g1.8xlarge 32 128 NVIDIA V100 * 4 16GB * 4 10 2,000,000 None 8 8 20
ecs.gn6v-c8g1.16xlarge 64 256 NVIDIA V100 * 8 16GB * 8 20 2,500,000 None 16 8 20
ecs.gn6v-c10g1.20xlarge 82 336 NVIDIA V100 * 8 16GB * 8 32 4,500,000 250,000 16 8 20
Note

vgn5i, vGPU-accelerated instance family

Features:
  • If you want your vgn5i instance to support graphics features such as OpenGL, you must purchase a GRID license from NVIDIA. Then, after the instance is created, you must manually install a GRID driver and activate the license.
  • Compute:
    • Uses NVIDIA P4 GPUs.
    • Uses vGPUs.
      • Supports the 1/8, 1/4, 1/2, and 1/1 compute 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 addresses.
    • Provides high network performance based on large computing capacity.
  • Applicable 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 vCPU Memory (GiB) GPU GPU memory Bandwidth (Gbit/s) Packet forwarding rate (pps) NIC queues ENIs Private IP addresses per ENI
ecs.vgn5i-m1.large 2 6 NVIDIA P4 * 1/8 8GB * 1/8 1 300,000 2 2 6
ecs.vgn5i-m2.xlarge 4 12 NVIDIA P4 * 1/4 8GB * 1/4 2 500,000 2 3 10
ecs.vgn5i-m4.2xlarge 8 24 NVIDIA P4 * 1/2 8GB * 1/2 3 800,000 2 4 10
ecs.vgn5i-m8.4xlarge 16 48 NVIDIA P4 * 1 8GB * 1 5 1,000,000 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.
  • Applicable scenarios:
    • Deep learning
    • Scientific computing applications such as computational fluid dynamics, computational 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 vCPU Memory (GiB) Local storage (GiB) GPU GPU memory Bandwidth (Gbit/s) Packet forwarding rate (pps) NIC queues ENIs Private IP addresses per ENI
ecs.gn5-c4g1.xlarge 4 30 440 NVIDIA P100 * 1 16GB * 1 3 300,000 1 3 10
ecs.gn5-c8g1.2xlarge 8 60 440 NVIDIA P100 * 1 16GB * 1 3 400,000 1 4 10
ecs.gn5-c4g1.2xlarge 8 60 880 NVIDIA P100 * 2 16GB * 2 5 1,000,000 2 4 10
ecs.gn5-c8g1.4xlarge 16 120 880 NVIDIA P100 * 2 16GB * 2 5 1,000,000 4 8 20
ecs.gn5-c28g1.7xlarge 28 112 440 NVIDIA P100 * 1 16GB * 1 5 1,000,000 8 8 20
ecs.gn5-c8g1.8xlarge 32 240 1760 NVIDIA P100 * 4 16GB * 4 10 2,000,000 8 8 20
ecs.gn5-c28g1.14xlarge 56 224 880 NVIDIA P100 * 2 16GB * 2 10 2,000,000 14 8 20
ecs.gn5-c8g1.14xlarge 54 480 3520 NVIDIA P100 * 8 16GB * 8 25 4,000,000 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 addresses.
    • Provides high network performance based on large computing capacity.
  • Applicable scenarios:
    • Deep learning inference
    • Server-side GPU compute workloads such as multi-media encoding and decoding
Instance types
Instance type vCPU Memory (GiB) GPU GPU memory Bandwidth (Gbit/s) Packet forwarding rate (pps) NIC queues ENIs Private IP addresses per ENI
ecs.gn5i-c2g1.large 2 8 NVIDIA P4 * 1 8GB * 1 1 100,000 2 2 6
ecs.gn5i-c4g1.xlarge 4 16 NVIDIA P4 * 1 8GB * 1 1.5 200,000 2 3 10
ecs.gn5i-c8g1.2xlarge 8 32 NVIDIA P4 * 1 8GB * 1 2 400,000 4 4 10
ecs.gn5i-c16g1.4xlarge 16 64 NVIDIA P4 * 1 8GB * 1 3 800,000 4 8 20
ecs.gn5i-c16g1.8xlarge 32 128 NVIDIA P4 * 2 8GB * 2 6 1,200,000 8 8 20
ecs.gn5i-c28g1.14xlarge 56 224 NVIDIA P4 * 2 8GB * 2 10 2,000,000 14 8 20
Note