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
- sgn7i-vws, vGPU-accelerated instance family with shared CPUs
- vgn7i-vws, vGPU-accelerated instance family
- gn7s, GPU-accelerated compute-optimized instance family
- gn7e, GPU-accelerated compute-optimized instance family
- gn7i, GPU-accelerated compute-optimized instance family
- gn7, GPU-accelerated compute-optimized instance family
- vgn6i and vgn6i-vws, vGPU-accelerated instance families
- gn6i, GPU-accelerated compute-optimized instance family
- gn6e, GPU-accelerated compute-optimized instance family
- gn6v, GPU-accelerated compute-optimized instance family
- Other available instance families (If these instance families are sold out, you can use the recommended ones.)
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 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 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 NVIDIA 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 enhanced SSDs (ESSDs).
Note For more information about the performance of cloud disks, see
EBS performance.
- 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 baseline/burst bandwidth (Gbit/s) | Packet forwarding rate (pps) | Network interface controller (NIC) queues | Elastic network interfaces (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 |
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 NVIDIA 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.
Note For more information about the performance of cloud disks, see
EBS performance.
- 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 |
gn7s, GPU-accelerated compute-optimized instance family
Features:
- This instance family uses new Intel Ice lake processors and NVIDIA A30 GPUs that are based on NVIDIA Ampere architecture. You can choose an appropriate mix of GPUs and CPU resources to meet various requirements for AI business.
- This instance family uses 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.
- 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.
Note For more information about the performance of cloud disks, see
EBS performance.
- 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 |
gn7e, GPU-accelerated compute-optimized instance family
Features:
- This instance family uses Intel Ice lake processors and NVIDIA A100 SXM4 80GB GPUs that are interconnected by using NVSwitches. You can choose an appropriate mix of GPUs and CPU resources to meet various AI business requirements.
- 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 A100 GPUs that have the following features:
- Innovative NVIDIA Ampere architecture
- Connections established between NVIDIA A100 GPUs by using NVSwitches
- Support for mixed-precision computing with 80 GB of HBM2 memory per GPU
- Uses 2.9 GHz Intel® Xeon® Platinum 8369B (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.
- Network:
- Supports IPv6.
- Provides high network performance based on large computing capacity.
- Supported scenarios:
- Small- and medium-scale AI training
- 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.
Important When 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 | GPU memory | Network bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues | ENIs | Private IP addresses per ENI |
---|
ecs.gn7e-c16g1.4xlarge | 16 | 125 | NVIDIA A100 * 1 | 80GB * 1 | 8 | 3,000,000 | 8 | 8 | 10 |
ecs.gn7e-c16g1.16xlarge | 64 | 500 | NVIDIA A100 * 4 | 80GB * 4 | 32 | 12,000,000 | 32 | 8 | 10 |
ecs.gn7e-c16g1.32xlarge | 128 | 1000 | NVIDIA A100 * 8 | 80GB * 8 | 64 | 24,000,000 | 32 | 16 | 15 |
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 NVIDIA 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 memory of up to 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 only ESSDs.
- 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 | 5 |
ecs.gn7i-c16g1.4xlarge | 16 | 60 | NVIDIA A10 * 1 | 24GB * 1 | 16 | 3,000,000 | 8 | 8 | 5 |
ecs.gn7i-c32g1.8xlarge | 32 | 188 | NVIDIA A10 * 1 | 24GB * 1 | 16 | 6,000,000 | 12 | 8 | 5 |
ecs.gn7i-c32g1.16xlarge | 64 | 376 | NVIDIA A10 * 2 | 24GB * 2 | 32 | 12,000,000 | 16 | 15 | 5 |
ecs.gn7i-c32g1.32xlarge | 128 | 752 | NVIDIA A10 * 4 | 24GB * 4 | 64 | 24,000,000 | 32 | 15 | 10 |
ecs.gn7i-c48g1.12xlarge | 48 | 310 | NVIDIA A10 * 1 | 24GB * 1 | 16 | 9,000,000 | 16 | 8 | 8 |
ecs.gn7i-c56g1.14xlarge | 56 | 346 | NVIDIA A10 * 1 | 24GB * 1 | 16 | 12,000,000 | 16 | 12 | 8 |
gn7, GPU-accelerated compute-optimized instance family
Features:
- Compute:
- Uses NVIDIA A100 GPUs. NVSwitches are used to establish connections between NVIDIA A100 GPUs. The GPUs have the following features:
- Innovative NVIDIA Ampere architecture
- 40 GB of 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 only ESSDs.
- 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 | GPU memory | Network bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues | ENIs |
---|
ecs.gn7-c12g1.3xlarge | 12 | 94 | NVIDIA A100 * 1 | 40GB * 1 | 4 | 2,500,000 | 4 | 8 |
ecs.gn7-c13g1.13xlarge | 52 | 378 | NVIDIA A100 * 4 | 40GB * 4 | 16 | 9,000,000 | 16 | 8 |
ecs.gn7-c13g1.26xlarge | 104 | 756 | NVIDIA A100 * 8 | 40GB * 8 | 30 | 18,000,000 | 16 | 15 |
vgn6i and vgn6i-vws, vGPU-accelerated instance families
vgn6i-vws:
- 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 a NVIDIA GRID driver, submit a ticket to apply for the GRID driver file and install the NVIDIA GRID driver separately. Alibaba Cloud does not charge additional fees for the license of the GRID driver.
vgn6i:
- If you want your vgn6i instance to support graphics features such as Open Graphics Library (OpenGL), you must purchase a GRID license from NVIDIA. After the instance is created, manually install a GRID driver and activate the license.
- Compute:
- Uses NVIDIA T4 GPUs.
- Uses vGPUs.
- Supports the 1/4 and 1/2 computing 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 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) | GPU | GPU memory | Network bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues (primary ENI/secondary ENI) | ENIs | Private IP addresses per ENI |
---|
ecs.vgn6i-m4.xlarge | 4 | 23 | NVIDIA T4 * 1/4 | 16GB * 1/4 | 2 | 500,000 | 4/2 | 3 | 10 |
ecs.vgn6i-m8.2xlarge | 10 | 46 | NVIDIA T4 * 1/2 | 16GB * 1/2 | 4 | 800,000 | 8/2 | 4 | 10 |
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 |
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.
- 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 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) | GPU | GPU memory | Network 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 | N/A | 2 | 2 | 10 |
ecs.gn6i-c8g1.2xlarge | 8 | 31 | NVIDIA T4 * 1 | 16GB * 1 | 5 | 800,000 | N/A | 2 | 2 | 10 |
ecs.gn6i-c16g1.4xlarge | 16 | 62 | NVIDIA T4 * 1 | 16GB * 1 | 6 | 1,000,000 | N/A | 4 | 3 | 10 |
ecs.gn6i-c24g1.6xlarge | 24 | 93 | NVIDIA T4 * 1 | 16GB * 1 | 7.5 | 1,200,000 | N/A | 6 | 4 | 10 |
ecs.gn6i-c40g1.10xlarge | 40 | 155 | NVIDIA T4 * 1 | 16GB * 1 | 10 | 1,600,000 | N/A | 16 | 10 | 10 |
ecs.gn6i-c24g1.12xlarge | 48 | 186 | NVIDIA T4 * 2 | 16GB * 2 | 15 | 2,400,000 | N/A | 12 | 6 | 10 |
ecs.gn6i-c24g1.24xlarge | 96 | 372 | NVIDIA T4 * 4 | 16GB * 4 | 30 | 4,800,000 | 250,000 | 24 | 8 | 10 |
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 of 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, 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 |
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 of 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, 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) | 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 | N/A | 4 | 4 | 10 |
ecs.gn6v-c8g1.8xlarge | 32 | 128 | NVIDIA V100 * 4 | 16GB * 4 | 10 | 2,000,000 | N/A | 8 | 8 | 20 |
ecs.gn6v-c8g1.16xlarge | 64 | 256 | NVIDIA V100 * 8 | 16GB * 8 | 20 | 2,500,000 | N/A | 16 | 8 | 20 |
ecs.gn6v-c10g1.20xlarge | 82 | 336 | NVIDIA V100 * 8 | 16GB * 8 | 32 | 4,500,000 | 250,000 | 16 | 8 | 20 |
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. After the instance is created, 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 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.
- Network:
- Supports IPv6.
- Provides high network performance based on large computing capacity.
- Supported scenarios:
- Real-time rendering for cloud gaming
- 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) | GPU | GPU memory | Network 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 |
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 Non-Volatile Memory Express (NVMe) SSDs.
- Is an instance family in which all instances are I/O optimized.
- Supports standard SSDs and ultra disks.
- Network:
- Provides high network performance based on large computing capacity.
- Supported scenarios:
- Deep learning
- Scientific computing applications, such as computational fluid dynamics, computational finance, genomics, and environmental analytics
- 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) | GPU | GPU memory | Network 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 |
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 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 |