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Instance types

Last updated:2021-03-19 14:46:28

Kingsoft Cloud provides a variety of GEC instance types for typical application scenarios. Different types of GEC instances use different hardware (GPU, CPU, memory, and disk) and network resource configurations. This topic details the application scenarios, models, and configuration information of GEC instance types.

GEC instance types

The following table describes GEC instance types.

GEC category Instance type Application scenario
Passthrough Common training and inference scenarios such as deep learning, voice, and graphics and image learning
vGPU Cloud rendering and small-scale, elastic and flexible AI application scenarios

GPU Inference II GN6I

GN6I GEC instances are applicable to inference scenarios and simple training scenarios.

Based on NVIDIA Tesla T4, each GPU has 16 GB GDDR6 graphic memory, 8.1 TFLOPS single precision FP32 computing capability, and 130 TOPS INT8 computing capability.

Instance characteristics:

  • Processor: 2.6 GHz Intel® Xeon® Gold 6240 Processor
  • Supported system disk: EBS 3.0
  • Supported data disk: EBS 3.0

The following table describes the GN6I GEC types and specifications.

Type GPU GPU graphic memory (GDDR6) vCPUs Memory (GiB) Packet sending/receiving capability (10,000 pps) Bandwidth (Gbps) Queues
GN6I.4A1 T4*1 16 GB*1 4 16 50 4 2
GN6I.8A1 T4*1 16 GB*1 8 32 80 5 2
GN6I.16A1 T4*1 16 GB*1 16 64 120 6 4
GN6I.16B2 T4*2 16 GB*2 16 64 120 6 4
GN6I.32B2 T4*2 16 GB*2 32 128 240 8 8
GN6I.32C4 T4*4 16 GB*4 32 128 240 8 8

GPU General Purpose Computing P3

P3 GEC instances are applicable to deep learning training scenarios and inference scenarios.

Based on NVIDIA Tesla P40, each GPU has 24 GB DDR5 GPU memory, 12 TFLOPS single precision FP32 computing capability, and 46 TOPS INT8 computing capability.

Instance characteristics:

  • Processor: 2.6 GHz Intel® Xeon® Processor E5-2690 v4
  • Supported system disk: local SSD
  • Supported data disk: local SSD and EBS 3.0

The following table describes the P3 GEC types and specifications.

Type GPUs (Tesla P40) GPU graphic memory (GDDR5) vCPUs Memory (DDR4) Data disk (local SSD) Packet sending/receiving capability (10,000 pps) Bandwidth (Gbps)
P3.28A1 1 24 GB*1 28 56 GB 1,000 GB 30 3
P3.56B2 2 24 GB*2 56 112 GB 2,000 GB 40 6
P3.56C4 4 24 GB*4 56 224 GB 4,000 GB 40 8

GPU Inference Computing P3I

P3I GEC instances are applicable to inference and prediction scenarios such as speech recognition, speech synthesis, and image recognition.

Based on NVIDIA Tesla P4, each GPU has 8 GB DDR5 GPU memory, 5.5 TFLOPS single precision FP32 computing capability, and 22 TOPS INT8 computing capability. In deep learning inference and prediction scenarios, the latency of a GPU instance is 15 times lower than that of a CPU, and the throughput is 60 times higher.

Instance characteristics:

  • Processor: 2.6 GHz Intel® Xeon® Processor E5-2690 v4
  • Supported system disk: local SSD
  • Supported data disk: local SSD and EBS 3.0

The following table describes the P3I GEC types and specifications.

Type GPU (Tesla P4) GPU graphic memory (GDDR5) vCPUs Memory (DDR4) Data disk (local SSD) Packet sending/receiving capability (10,000 pps) Bandwidth (Gbps)
P3I.14B1 1 8 GB*1 14 120 GB 500 GB 20 3
P3I.28C2 2 8 GB*2 28 240 GB 1,000 GB 30 6

GPU Inference Computing P3IN

Instance characteristics:

  • Processor: 2.6 GHz Intel® Xeon® Processor E5-2690 v4
  • Supported system disk: local SSD
  • Supported data disk: local SSD and EBS 3.0

P3IN GEC instances use the same hardware and are applicable to the same scenarios as P3I GEC instances. The following table describes the P3IN GEC types and specifications.

Type GPU (Tesla P4) GPU graphic memory (GDDR5) vCPUs Memory (DDR4) Data disk (local SSD) Packet sending/receiving capability (10,000 pps) Bandwidth (Gbps)
P3IN.4A1 1 8 GB*1 4 16 GB 120 GB 10 1.5
P3IN.8B1 1 8 GB*1 8 32 GB 180 GB 20 1.5
P3IN.16C2 2 8 GB*2 16 64 GB 360 GB 30 3
P3IN.32D4 4 8 GB*4 32 128 GB 720 GB 40 6

GPU General Purpose Computing P4V

P4V GEC instances are applicable to deep learning training scenarios and inference scenarios.

Based on NVIDIA Tesla V100, each GPU has 16 GB HBM2 GPU memory, 15 TFLOPS single precision FP32 computing capability, and 125 TFLOPS mixed-precision computing capability.

Instance characteristics:

  • Processor: 2.6 GHz Intel® Xeon® Processor E5-2690 v4
  • Supported system disk: local SSD
  • Supported data disk: local SSD and EBS 3.0

The following table describes the P4V GEC types and specifications.

Type GPU (Tesla V100) GPU graphic memory (HBM2) vCPUs Memory (DDR4) Data disk (local SSD) Packet sending/receiving capability (10,000 pps) Bandwidth (Gbps)
P4V.8A1 1 16 GB*1 8 32 GB 240 GB 20 1.5
P4V.16B2 2 16 GB*2 16 64 GB 480 GB 30 3
P4V.28C4 4 16 GB*4 28 128 GB 960 GB 30 6
P4V.56D8 8 16 GB*8 56 256 GB 1,920 GB 40 8

GPU Virtualization vGN5

vGN5 GEC instances are applicable to the following scenarios:

  • Real-time cloud rendering for cloud games
  • Real-time cloud rendering for AR and VR
  • AI (deep learning and machine learning)

Instance characteristics:

  • GPU: NVIDIA P4 GPU
  • Processor: 2.6 GHz Intel® Xeon® E5-2690 v4 (Broadwell)
  • Supported system disk: local SSD
  • Supported data disk: local SSD and EBS 3.0
  • vGPU types
    • vCS: used for deep learning and supports 1*Tesla P4 and 1/2*Tesla P4 instances
    • vPC: used for graphics and image processing and supports 1/4*Tesla P4 and 1/8*Tesla P4 instances

The following table describes the vGN5 GEC types and specifications.

Type GPU (Tesla P4) GPU graphic memory (GDDR5) vCPUs Memory (DDR4) Data disk (local SSD) Packet sending/receiving capability (10,000 pps) Bandwidth (Gbps)
vGN5.vCS-8B2 1/2 4 GB 8 48 GB 400 GB 20 2
vGN5.vPC-4C4 1/4 2 GB 4 24 GB 200 GB 10 1
vGN5.vPC-2D8 1/8 1 GB 2 12 GB 100 GB 10 1

vCS is applicable for CUDA computing such as AI inference, and vPC is applicable for graphics and image processing. For more information about vGN5 configuration, see vGPU user guide.

GPU Virtualization vGN6

vGN6 GEC instances are applicable to the following scenarios:

  • Real-time cloud rendering for cloud games
  • Real-time cloud rendering for AR and VR
  • AI (deep learning and machine learning)

Instance characteristics:

  • GPU: NVIDIA T4 GPU
  • Processor: 2.6 GHz Intel® Xeon® Gold 6240 Processor
  • Supported system disk: EBS 3.0
  • Supported data disk: EBS 3.0
  • vGPU types
    • vCS: used for deep learning and supports 1/2*Tesla T4 and 1/4*Tesla T4 instances
    • vPC: used for graphics and image processing and supports 1/8*Tesla T4 instances

The following table describes the vGN6 GEC types and specifications.

Type GPU (Tesla T4) GPU graphic memory (GDDR6) vCPUs Memory (DDR4) Packet sending/receiving capability (10,000 pps) Bandwidth (Gbps)
vGN6.vCS-10B2 1/2 8 GB 10 40 GB 80 3
vGN6.vCS-4C4 1/4 4 GB 4 20 GB 50 2
vGN6.vPC-2D8 1/8 2 GB 2 10 GB 30 1

vCS is applicable for CUDA computing such as AI inference, and vPC is applicable for graphics and image processing. For more information about vGN6 configuration, see vGPU user guide.

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