Instances of vGPU-accelerated instance families provide high-performance graphics processing and GPU-accelerated computing capabilities and are suitable for graphics acceleration and rendering scenarios and general-purpose computing scenarios. This topic describes the features of vGPU-accelerated instance families of Elastic Compute Service (ECS) and lists the instance types of each instance family.
sgn8ia, vGPU-accelerated instance family
Introduction:
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, this instance family accelerates the speed of data storage and model loading.
This instance family comes with an 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.
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 AMD Genoa processors with high clock speeds, such as animation and film production, cloud gaming, and mechanical design
Compute:
Uses NVIDIA Lovelace GPUs that have the following features:
Large GPU memory and multiple GPU slicing solutions
Support for acceleration features, such as vGPU, RTX, and TensorRT, to provide diversified business support
Uses AMD Genoa processors that deliver a clock speed of 3.4 GHz to 3.75 GHz to provide high computing power for 3D modeling.
Storage:
Is an instance family in which all instances are I/O optimized.
Supports Enterprise SSDs (ESSDs) and ESSD AutoPL disks.
Network:
Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.
Provides high network performance based on large computing capacity.
sgn8ia instance types
Instance type | vCPUs | Memory (GiB) | GPU memory | Network baseline bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues | ENIs | Private IPv4/IPv6 addresses per ENI | Maximum disks | Disk baseline IOPS | Disk baseline BPS (MB/s) |
ecs.sgn8ia-m2.xlarge | 4 | 16 | 2 GB | 2.5 | 1,000,000 | 4 | 4 | 15/15 | 9 | 30,000 | 244 |
ecs.sgn8ia-m4.2xlarge | 8 | 32 | 4 GB | 4 | 1,600,000 | 8 | 4 | 15/15 | 9 | 45,000 | 305 |
ecs.sgn8ia-m8.4xlarge | 16 | 64 | 8 GB | 7 | 2,000,000 | 16 | 8 | 30/30 | 17 | 60,000 | 427 |
ecs.sgn8ia-m16.8xlarge | 32 | 128 | 16 GB | 10 | 3,000,000 | 32 | 8 | 30/30 | 33 | 80,000 | 610 |
ecs.sgn8ia-m24.12xlarge | 48 | 192 | 24 GB | 16 | 4,500,000 | 48 | 8 | 30/30 | 33 | 120,000 | 1,000 |
ecs.sgn8ia-m48.24xlarge | 96 | 384 | 48 GB | 32 | 9,000,000 | 64 | 15 | 30/30 | 33 | 24,000 | 2,000 |
The columns related to GPUs in the preceding table are for vGPUs that are sliced by using the vGPU slicing technology.
The memory and GPU memory of an sgn8ia instance are exclusive to the instance. The CPUs of the instance are shared resources with an overcommit ratio of approximately 1:1.5. If you have special requirements for the CPU computing power, we recommend that you use GPU-accelerated dedicated instance families, such as gn7i GPU-accelerated compute-optimized instances.
sgn7i-vws, vGPU-accelerated instance family with shared CPUs
Introduction:
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 an 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.
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
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 ESSDs and ESSD AutoPL disks.
Network:
Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.
Provides high network performance based on large computing capacity.
sgn7i-vws instance types
Instance type | vCPUs | Memory (GiB) | GPUs | GPU memory | Network baseline/burst bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues | ENIs | Private IPv4 addresses per ENI | IPv6 addresses per ENI |
ecs.sgn7i-vws-m2.xlarge | 4 | 15.5 | NVIDIA A10 * 1/12 | 24GB * 1/12 | 1.5/5 | 500,000 | 4 | 2 | 2 | 1 |
ecs.sgn7i-vws-m4.2xlarge | 8 | 31 | NVIDIA A10 * 1/6 | 24GB * 1/6 | 2.5/10 | 1,000,000 | 4 | 4 | 6 | 1 |
ecs.sgn7i-vws-m8.4xlarge | 16 | 62 | NVIDIA A10 * 1/3 | 24GB * 1/3 | 5/20 | 2,000,000 | 8 | 4 | 10 | 1 |
ecs.sgn7i-vws-m2s.xlarge | 4 | 8 | NVIDIA A10 * 1/12 | 24GB * 1/12 | 1.5/5 | 500,000 | 4 | 2 | 2 | 1 |
ecs.sgn7i-vws-m4s.2xlarge | 8 | 16 | NVIDIA A10 * 1/6 | 24GB * 1/6 | 2.5/10 | 1,000,000 | 4 | 4 | 6 | 1 |
ecs.sgn7i-vws-m8s.4xlarge | 16 | 32 | NVIDIA A10 * 1/3 | 24GB * 1/3 | 5/20 | 2,000,000 | 8 | 4 | 10 | 1 |
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.
vgn7i-vws, vGPU-accelerated instance family
Introduction:
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 an 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.
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
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 ESSDs and ESSD AutoPL disks.
Network:
Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.
Provides high network performance based on large computing capacity.
vgn7i-vws instance types
Instance type | vCPUs | Memory (GiB) | GPUs | GPU memory | Network baseline bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues | ENIs | Private IPv4 addresses per ENI | IPv6 addresses per ENI |
ecs.vgn7i-vws-m4.xlarge | 4 | 30 | NVIDIA A10 * 1/6 | 24GB * 1/6 | 3 | 1,000,000 | 4 | 4 | 10 | 1 |
ecs.vgn7i-vws-m8.2xlarge | 10 | 62 | NVIDIA A10 * 1/3 | 24GB * 1/3 | 5 | 2,000,000 | 8 | 6 | 10 | 1 |
ecs.vgn7i-vws-m12.3xlarge | 14 | 93 | NVIDIA A10 * 1/2 | 24GB * 1/2 | 8 | 3,000,000 | 8 | 6 | 15 | 1 |
ecs.vgn7i-vws-m24.7xlarge | 30 | 186 | NVIDIA A10 * 1 | 24GB * 1 | 16 | 6,000,000 | 12 | 8 | 30 | 1 |
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.
vgn6i-vws, vGPU-accelerated instance family
In light of the NVIDIA GRID driver upgrade, Alibaba Cloud upgrades the vgn6i instance family to the vgn6i-vws instance family. The vgn6i-vws instance family uses the latest NVIDIA GRID driver and provides an NVIDIA GRID vWS license. To apply for free images for which the NVIDIA GRID driver is pre-installed, submit a ticket.
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.
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
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 standard SSDs and ultra disks.
Network:
Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.
Provides high network performance based on large computing capacity.
vgn6i-vws instance types
Instance type | vCPUs | Memory (GiB) | GPUs | GPU memory | Network baseline bandwidth (Gbit/s) | Packet forwarding rate (pps) | NIC queues | ENIs | Private IPv4 addresses per ENI | IPv6 addresses per ENI |
ecs.vgn6i-m4-vws.xlarge | 4 | 23 | NVIDIA T4 * 1/4 | 16GB * 1/4 | 2 | 500,000 | 4/2 | 3 | 10 | 1 |
ecs.vgn6i-m8-vws.2xlarge | 10 | 46 | NVIDIA T4 * 1/2 | 16GB * 1/2 | 4 | 800,000 | 8/2 | 4 | 10 | 1 |
ecs.vgn6i-m16-vws.5xlarge | 20 | 92 | NVIDIA T4 * 1 | 16GB * 1 | 7.5 | 1,200,000 | 6 | 4 | 10 | 1 |
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.