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.
Recommended instance families
Other available instance families (If the following instance families are sold out, you can use the recommended instance families.)
sgn7i-vws, vGPU-accelerated instance family with shared CPUs
Features:
This instance family uses the third-generation SHENLONG architecture to provide predictable and consistent ultra-high performance. This instance family utilizes fast path acceleration on chips to improve storage performance, network performance, and computing stability by an order of magnitude. This way, data storage and model loading can be performed more quickly.
Instances of this 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 provide data isolation and performance assurance.
NoteIf you want to use exclusive CPU resources, select the vgn7i-vws instance family.
This instance family comes with a NVIDIA GRID vWS license and provides certified graphics acceleration capabilities for Computer Aided Design (CAD) software to meet the requirements of professional graphic design. Instances of this instance family can serve 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 TensorRT) to provide diversified 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 only ESSDs and ESSD AutoPL disks.
Network:
Supports IPv6.
Provides high network performance based on large computing capacity.
Supported 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 | vCPUs | 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 |
The GPU column in the preceding table indicates the GPU model and GPU slicing information for each instance type. Each GPU can be sliced into multiple GPU partitions, and each GPU partition can be allocated as a vGPU to an instance. Example:
NVIDIA A10 * 1/12
.NVIDIA A10
is the GPU model.1/12
indicates that a GPU is sliced into 12 GPU partitions, and each GPU partition can be allocated as a vGPU to an instance.You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.
For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.
vgn7i-vws, vGPU-accelerated instance family
Features:
This instance family uses the third-generation SHENLONG architecture to provide predictable and consistent ultra-high performance. This instance family utilizes fast path acceleration on chips to improve storage performance, network performance, and computing stability by an order of magnitude. This way, data storage and model loading can be performed more quickly.
This instance family comes with a NVIDIA GRID vWS license and provides certified graphics acceleration capabilities for CAD software to meet the requirements of professional graphic design. Instances of this instance family can serve 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 TensorRT) to provide diversified 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 only ESSDs and ESSD AutoPL disks.
Network:
Supports IPv6.
Provides high network performance based on large computing capacity.
Supported 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 | vCPUs | Memory (GiB) | GPU | GPU memory | Network 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 |
The GPU column in the preceding table indicates the GPU model and GPU slicing information for each instance type. Each GPU can be sliced into multiple GPU partitions, and each GPU partition can be allocated as a vGPU to an instance. Example:
NVIDIA A10 * 1/6
.NVIDIA A10
is the GPU model.1/6
indicates that a GPU is sliced into six GPU partitions, and each GPU partition can be allocated as a vGPU to an instance.You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.
For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.
gn7e, GPU-accelerated compute-optimized instance family
Features:
You can select instance types that comprise appropriate mixes of GPUs and vCPUs to meet your business requirements in AI scenarios.
This instance family uses the third-generation SHENLONG architecture and doubles the average bandwidths of virtual private clouds (VPCs), networks, and disks compared with instance families of the previous generation.
Storage:
Is an instance family in which all instances are I/O optimized.
Supports only ESSDs and ESSD AutoPL disks.
Network:
Supports IPv6.
Provides high network performance based on large computing capacity.
Supported scenarios:
Small- and medium-scale AI training workloads
High-performance computing (HPC) business accelerated by using Compute Unified Device Architecture (CUDA)
AI inference tasks that require high GPU processing capabilities or large amounts of GPU memory
Deep learning applications such as training applications of AI algorithms used in image classification, autonomous vehicles, and speech recognition
Scientific computing applications that require robust GPU computing capabilities such as computational fluid dynamics, computational finance, molecular dynamics, and environmental analytics
ImportantWhen you use AI training services that feature a high communication load, such as transformer models, you must enable NVLink for GPU-to-GPU communication. Otherwise, data may be damaged due to unpredictable failures that are caused by large-scale data transmission over Peripheral Component Interconnect Express (PCIe) links. If you do not understand the topology of the communication links that are used for AI training services, submit a ticket to obtain technical support.
Instance types
Instance type | vCPUs | Memory (GiB) | GPU memory | Network bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues | ENIs | Private IP addresses per ENI |
ecs.gn7e-c16g1.4xlarge | 16 | 125 | 80GB * 1 | 8 | 3,000,000 | 8 | 8 | 10 |
ecs.gn7e-c16g1.16xlarge | 64 | 500 | 80GB * 4 | 32 | 12,000,000 | 32 | 8 | 10 |
ecs.gn7e-c16g1.32xlarge | 128 | 1000 | 80GB * 8 | 64 | 24,000,000 | 32 | 16 | 15 |
You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.
For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.
gn7i, GPU-accelerated compute-optimized instance family
Features:
This instance family uses the third-generation SHENLONG architecture to provide predictable and consistent ultra-high performance. This instance family utilizes fast path acceleration on chips 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 TensorRT
Uses 2.9 GHz Intel® Xeon® Scalable (Ice Lake) processors that deliver an all-core turbo frequency of 3.5 GHz.
Provides up to 752 GiB of memory, 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 only ESSDs and ESSD AutoPL disks.
Network:
Supports IPv6.
Provides high network performance based on large computing capacity.
Supported 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 | vCPUs | Memory (GiB) | GPU | GPU memory | Network bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues | ENIs | Private IP addresses per ENI |
ecs.gn7i-c8g1.2xlarge | 8 | 30 | NVIDIA A10 * 1 | 24GB * 1 | 16 | 1,600,000 | 8 | 4 | 15 |
ecs.gn7i-c16g1.4xlarge | 16 | 60 | NVIDIA A10 * 1 | 24GB * 1 | 16 | 3,000,000 | 8 | 8 | 30 |
ecs.gn7i-c32g1.8xlarge | 32 | 188 | NVIDIA A10 * 1 | 24GB * 1 | 16 | 6,000,000 | 12 | 8 | 30 |
ecs.gn7i-c32g1.16xlarge | 64 | 376 | NVIDIA A10 * 2 | 24GB * 2 | 32 | 12,000,000 | 16 | 15 | 30 |
ecs.gn7i-c32g1.32xlarge | 128 | 752 | NVIDIA A10 * 4 | 24GB * 4 | 64 | 24,000,000 | 32 | 15 | 30 |
ecs.gn7i-c48g1.12xlarge | 48 | 310 | NVIDIA A10 * 1 | 24GB * 1 | 16 | 9,000,000 | 16 | 8 | 30 |
ecs.gn7i-c56g1.14xlarge | 56 | 346 | NVIDIA A10 * 1 | 24GB * 1 | 16 | 12,000,000 | 16 | 12 | 30 |
ecs.gn7i-2x.8xlarge | 32 | 128 | NVIDIA A10 * 2 | 24GB * 2 | 16 | 6,000,000 | 16 | 8 | 30 |
ecs.gn7i-4x.8xlarge | 32 | 128 | NVIDIA A10 * 4 | 24GB * 4 | 16 | 6,000,000 | 16 | 8 | 30 |
ecs.gn7i-4x.16xlarge | 64 | 256 | NVIDIA A10 * 4 | 24GB * 4 | 32 | 12,000,000 | 32 | 8 | 30 |
ecs.gn7i-8x.32xlarge | 128 | 512 | NVIDIA A10 * 8 | 24GB * 8 | 64 | 24,000,000 | 32 | 16 | 30 |
ecs.gn7i-8x.16xlarge | 64 | 256 | NVIDIA A10 * 8 | 24GB * 8 | 32 | 12,000,000 | 32 | 8 | 30 |
You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.
You can change the following instance types only to ecs.gn7i-c8g1.2xlarge or ecs.gn7i-c16g1.4xlarge: ecs.gn7i-2x.8xlarge, ecs.gn7i-4x.8xlarge, ecs.gn7i-4x.16xlarge, ecs.gn7i-8x.32xlarge, and ecs.gn7i-8x.16xlarge.
For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.
gn7s, GPU-accelerated compute-optimized instance family
To use the gn7s instance family, submit a ticket.
Features:
This instance family uses the latest Intel Ice Lake processors and NVIDIA A30 GPUs that are based on NVIDIA Ampere architecture. You can select instance types that comprise appropriate mixes of GPUs and vCPUs to meet your business requirements in AI scenarios.
This instance family uses the third-generation SHENLONG architecture and doubles the average bandwidths of VPCs, networks, and disks compared with instance families of the previous generation.
Compute:
Uses NVIDIA A30 GPUs that have the following features:
Innovative NVIDIA Ampere architecture
Support for the multi-instance GPU (MIG) feature and acceleration features (based on second-generation Tensor cores) to provide diversified business support
Uses 2.9 GHz Intel® Xeon® Scalable (Ice Lake) processors that deliver an all-core turbo frequency of 3.5 GHz.
Improves memory sizes significantly from instance families of the previous generation.
Storage: Supports only ESSDs and ESSD AutoPL disks.
Network:
Supports IPv6.
Provides high network performance based on large computing capacity.
Supported scenarios: concurrent AI inference tasks that require high-performance CPUs, memory, and GPUs, such as image recognition, speech recognition, and behavior identification.
Instance types
Instance type | vCPUs | Memory (GiB) | GPU | GPU memory | Network bandwidth (Gbit/s) | Packet forwarding rate (pps) | IPv6 addresses per ENI | NIC queues | ENIs |
ecs.gn7s-c8g1.2xlarge | 8 | 60 | NVIDIA A30 * 1 | 24GB * 1 | 16 | 6,000,000 | 1 | 12 | 8 |
ecs.gn7s-c16g1.4xlarge | 16 | 120 | NVIDIA A30 * 1 | 24GB * 1 | 16 | 6,000,000 | 1 | 12 | 8 |
ecs.gn7s-c32g1.8xlarge | 32 | 250 | NVIDIA A30 * 1 | 24GB * 1 | 16 | 6,000,000 | 1 | 12 | 8 |
ecs.gn7s-c32g1.16xlarge | 64 | 500 | NVIDIA A30 * 2 | 24GB * 2 | 32 | 12,000,000 | 1 | 16 | 15 |
ecs.gn7s-c32g1.32xlarge | 128 | 1000 | NVIDIA A30 * 4 | 24GB * 4 | 64 | 24,000,000 | 1 | 32 | 15 |
ecs.gn7s-c48g1.12xlarge | 48 | 380 | NVIDIA A30 * 1 | 24GB * 1 | 16 | 6,000,000 | 1 | 12 | 8 |
ecs.gn7s-c56g1.14xlarge | 56 | 440 | NVIDIA A30 * 1 | 24GB * 1 | 16 | 6,000,000 | 1 | 12 | 8 |
You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.
For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.
gn7, GPU-accelerated compute-optimized instance family
Features:
Storage:
Is an instance family in which all instances are I/O optimized.
Supports only ESSDs and ESSD AutoPL disks.
Network:
Supports IPv6.
Provides high network performance based on large computing capacity.
Supported scenarios:
Deep learning applications such as training applications of AI algorithms used in image classification, autonomous vehicles, and speech recognition
Scientific computing applications that require robust GPU computing capabilities such as computational fluid dynamics, computational finance, molecular dynamics, and environmental analytics
Instance types
Instance type | vCPUs | Memory (GiB) | GPU memory | Network bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues | ENIs |
ecs.gn7-c12g1.3xlarge | 12 | 94 | 40GB * 1 | 4 | 2,500,000 | 4 | 8 |
ecs.gn7-c13g1.13xlarge | 52 | 378 | 40GB * 4 | 16 | 9,000,000 | 16 | 8 |
ecs.gn7-c13g1.26xlarge | 104 | 756 | 40GB * 8 | 30 | 18,000,000 | 16 | 15 |
You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.
For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.
vgn6i and vgn6i-vws, vGPU-accelerated instance families
Features:
In light of the NVIDIA GRID driver upgrade, Alibaba Cloud upgrades the vgn6i instance family to vgn6i-vws instance family. The vgn6i-vws instance family uses the latest NVIDIA GRID driver and provides a NVIDIA GRID vWS license. Submit a ticket to apply for free images that have the NVIDIA GRID driver pre-installed.
To use other public images or custom images that do not contain an NVIDIA GRID driver, submit a ticket to apply for the GRID driver file and install the NVIDIA GRID driver. Alibaba Cloud does not charge additional license fees for the GRID driver.
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.
Provides high network performance based on large computing capacity.
Supported scenarios:
Real-time rendering for cloud gaming
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 | vCPUs | Memory (GiB) | GPU | GPU memory | Network bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues (primary NIC/secondary NIC) | ENIs | Private IP addresses per ENI |
ecs.vgn6i-m4-vws.xlarge | 4 | 23 | NVIDIA T4 * 1/4 | 16GB * 1/4 | 2 | 500,000 | 4/2 | 3 | 10 |
ecs.vgn6i-m8-vws.2xlarge | 10 | 46 | NVIDIA T4 * 1/2 | 16GB * 1/2 | 4 | 800,000 | 8/2 | 4 | 10 |
ecs.vgn6i-m16-vws.5xlarge | 20 | 92 | NVIDIA T4 * 1 | 16GB * 1 | 7.5 | 1,200,000 | 6 | 4 | 10 |
The GPU column in the preceding table indicates the GPU model and GPU slicing information for each instance type. Each GPU can be sliced into multiple GPU partitions, and each GPU partition can be allocated as a vGPU to an instance. Example:
NVIDIA T4 * 1/4
.NVIDIA T4
is the GPU model.1/4
indicates that a GPU is sliced into four GPU partitions, and each GPU partition can be allocated as a vGPU to an instance.You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.
For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.
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 ESSDs, ESSD AutoPL disks, standard SSDs, and ultra disks.
Network:
Supports IPv6.
Provides high network performance based on large computing capacity.
Supported 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 gaming
Real-time rendering for AR and VR applications
Graphics workstations or graphics-heavy computing
GPU-accelerated databases
High-performance computing
Instance types
Instance type | vCPUs | Memory (GiB) | GPU | GPU memory | Network bandwidth (Gbit/s) | Packet forwarding rate (pps) | Storage baseline 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 |
You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.
For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.
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 NVIDIA Volta architecture
32 GB HBM2 memory (900 GB/s bandwidth) per GPU
5,120 CUDA cores per GPU
640 Tensor cores per GPU
Support for up to six NVLink bidirectional connections, which each provide a bandwidth of 25 GB/s in each direction for a total bandwidth of 300 GB/s (6 × 25 × 2 = 300)
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, ESSD AutoPL disks, standard SSDs, and ultra disks.
Network:
Supports IPv6.
Provides high network performance based on large computing capacity.
Supported 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 analytics
Instance types
Instance type | vCPUs | Memory (GiB) | GPU | GPU memory | Network 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 |
You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.
For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.
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 NVIDIA Volta architecture
16 GB HBM2 memory (900 GB/s bandwidth) per GPU
5,120 CUDA cores per GPU
640 Tensor cores per GPU
Support for up to six NVLink bidirectional connections, which each provide a bandwidth of 25 GB/s in each direction for a total bandwidth of 300 GB/s (6 × 25 × 2 = 300)
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, ESSD AutoPL disks, standard SSDs, and ultra disks.
Network:
Supports IPv6.
Provides high network performance based on large computing capacity.
Supported 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 analytics
Instance types
Instance type | vCPUs | Memory (GiB) | GPU | GPU memory | Network bandwidth (Gbit/s) | Packet forwarding rate (pps) | Storage baseline 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 |
You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.
For more information about these specifications, see the "Instance type specifications" section in Instance family.
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.
Supported scenarios:
Deep learning inference
Server-side GPU compute workloads such as multi-media encoding and decoding
Instance types
Instance type | vCPUs | Memory (GiB) | GPU | GPU memory | Network 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 |
You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.
For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.