2.238.0

enum AcceleratorName

LanguageType name
.NETAmazon.CDK.AWS.EC2.AcceleratorName
Gogithub.com/aws/aws-cdk-go/awscdk/v2/awsec2#AcceleratorName
Javasoftware.amazon.awscdk.services.ec2.AcceleratorName
Pythonaws_cdk.aws_ec2.AcceleratorName
TypeScript (source)aws-cdk-lib » aws_ec2 » AcceleratorName

Specific hardware accelerator models supported by EC2.

Defines exact accelerator models that can be required or excluded when selecting instance types.

Example

declare const vpc: ec2.Vpc;

const securityGroup = new ec2.SecurityGroup(this, 'SecurityGroup', {
  vpc,
  description: 'Security group for managed instances',
});

const miCapacityProvider = new ecs.ManagedInstancesCapacityProvider(this, 'MICapacityProvider', {
  subnets: vpc.privateSubnets,
  securityGroups: [securityGroup],
  instanceRequirements: {
    // Required: CPU and memory constraints
    vCpuCountMin: 2,
    vCpuCountMax: 8,
    memoryMin: Size.gibibytes(4),
    memoryMax: Size.gibibytes(32),

    // CPU preferences
    cpuManufacturers: [ec2.CpuManufacturer.INTEL, ec2.CpuManufacturer.AMD],
    instanceGenerations: [ec2.InstanceGeneration.CURRENT],

    // Instance type filtering
    allowedInstanceTypes: ['m5.*', 'c5.*'],

    // Performance characteristics
    burstablePerformance: ec2.BurstablePerformance.EXCLUDED,
    bareMetal: ec2.BareMetal.EXCLUDED,

    // Accelerator requirements (for ML/AI workloads)
    acceleratorTypes: [ec2.AcceleratorType.GPU],
    acceleratorManufacturers: [ec2.AcceleratorManufacturer.NVIDIA],
    acceleratorNames: [ec2.AcceleratorName.T4, ec2.AcceleratorName.V100],
    acceleratorCountMin: 1,

    // Storage requirements
    localStorage: ec2.LocalStorage.REQUIRED,
    localStorageTypes: [ec2.LocalStorageType.SSD],
    totalLocalStorageGBMin: 100,

    // Network requirements
    networkInterfaceCountMin: 2,
    networkBandwidthGbpsMin: 10,

    // Cost optimization
    onDemandMaxPricePercentageOverLowestPrice: 10,
  },
});

Members

NameDescription
A100NVIDIA A100 GPU.
K80NVIDIA K80 GPU.
M60NVIDIA M60 GPU.
RADEON_PRO_V520AMD Radeon Pro V520 GPU.
T4NVIDIA T4 GPU.
V100NVIDIA V100 GPU.
VU9PXilinx VU9P FPGA.
A10GNVIDIA A10G GPU.
H100NVIDIA H100 GPU.
INFERENTIAAWS Inferentia chips.
K520NVIDIA GRID K520 GPU.
T4GNVIDIA T4G GPUs.
L40SNVIDIA L40S GPU for AI inference and graphics workloads.
L4NVIDIA L4 GPU for AI inference and graphics workloads.
GAUDI_HL_205Habana Gaudi HL-205 accelerator for deep learning training.
INFERENTIA2AWS Inferentia2 chips for high-performance ML inference.
TRAINIUMAWS Trainium chips for high-performance ML training.
TRAINIUM2AWS Trainium2 chips for high-performance ML training.
U30Xilinx U30 media transcoding accelerator for video processing.

A100

NVIDIA A100 GPU.

K80

NVIDIA K80 GPU.

M60

NVIDIA M60 GPU.

RADEON_PRO_V520

AMD Radeon Pro V520 GPU.

T4

NVIDIA T4 GPU.

V100

NVIDIA V100 GPU.

VU9P

Xilinx VU9P FPGA.

A10G

NVIDIA A10G GPU.

H100

NVIDIA H100 GPU.

INFERENTIA

AWS Inferentia chips.

K520

NVIDIA GRID K520 GPU.

T4G

NVIDIA T4G GPUs.

L40S

NVIDIA L40S GPU for AI inference and graphics workloads.

L4

NVIDIA L4 GPU for AI inference and graphics workloads.

GAUDI_HL_205

Habana Gaudi HL-205 accelerator for deep learning training.

INFERENTIA2

AWS Inferentia2 chips for high-performance ML inference.

TRAINIUM

AWS Trainium chips for high-performance ML training.

TRAINIUM2

AWS Trainium2 chips for high-performance ML training.

U30

Xilinx U30 media transcoding accelerator for video processing.

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