Enum AcceleratorName

Specific hardware accelerator models supported by EC2.

Namespace: Amazon.CDK.AWS.EC2

Assembly: Amazon.CDK.Lib.dll

Syntax (csharp)

public enum AcceleratorName

Syntax (vb)

Public Enum AcceleratorName

Remarks

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

ExampleMetadata: infused

Examples

Vpc vpc;


             var securityGroup = new SecurityGroup(this, "SecurityGroup", new SecurityGroupProps {
                 Vpc = vpc,
                 Description = "Security group for managed instances"
             });

             var miCapacityProvider = new ManagedInstancesCapacityProvider(this, "MICapacityProvider", new ManagedInstancesCapacityProviderProps {
                 Subnets = vpc.PrivateSubnets,
                 SecurityGroups = new [] { securityGroup },
                 InstanceRequirements = new InstanceRequirementsConfig {
                     // Required: CPU and memory constraints
                     VCpuCountMin = 2,
                     VCpuCountMax = 8,
                     MemoryMin = Size.Gibibytes(4),
                     MemoryMax = Size.Gibibytes(32),

                     // CPU preferences
                     CpuManufacturers = new [] { CpuManufacturer.INTEL, CpuManufacturer.AMD },
                     InstanceGenerations = new [] { InstanceGeneration.CURRENT },

                     // Instance type filtering
                     AllowedInstanceTypes = new [] { "m5.*", "c5.*" },

                     // Performance characteristics
                     BurstablePerformance = BurstablePerformance.EXCLUDED,
                     BareMetal = BareMetal.EXCLUDED,

                     // Accelerator requirements (for ML/AI workloads)
                     AcceleratorTypes = new [] { AcceleratorType.GPU },
                     AcceleratorManufacturers = new [] { AcceleratorManufacturer.NVIDIA },
                     AcceleratorNames = new [] { AcceleratorName.T4, AcceleratorName.V100 },
                     AcceleratorCountMin = 1,

                     // Storage requirements
                     LocalStorage = LocalStorage.REQUIRED,
                     LocalStorageTypes = new [] { LocalStorageType.SSD },
                     TotalLocalStorageGBMin = 100,

                     // Network requirements
                     NetworkInterfaceCountMin = 2,
                     NetworkBandwidthGbpsMin = 10,

                     // Cost optimization
                     OnDemandMaxPricePercentageOverLowestPrice = 10
                 }
             });

Synopsis

Fields

A100	NVIDIA A100 GPU.
A10G	NVIDIA A10G GPU.
GAUDI_HL_205	Habana Gaudi HL-205 accelerator for deep learning training.
H100	NVIDIA H100 GPU.
INFERENTIA	AWS Inferentia chips.
INFERENTIA2	AWS Inferentia2 chips for high-performance ML inference.
K520	NVIDIA GRID K520 GPU.
K80	NVIDIA K80 GPU.
L4	NVIDIA L4 GPU for AI inference and graphics workloads.
L40S	NVIDIA L40S GPU for AI inference and graphics workloads.
M60	NVIDIA M60 GPU.
RADEON_PRO_V520	AMD Radeon Pro V520 GPU.
T4	NVIDIA T4 GPU.
T4G	NVIDIA T4G GPUs.
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.
V100	NVIDIA V100 GPU.
VU9P	Xilinx VU9P FPGA.

Fields

Name	Description
A100	NVIDIA A100 GPU.
A10G	NVIDIA A10G GPU.
GAUDI_HL_205	Habana Gaudi HL-205 accelerator for deep learning training.
H100	NVIDIA H100 GPU.
INFERENTIA	AWS Inferentia chips.
INFERENTIA2	AWS Inferentia2 chips for high-performance ML inference.
K520	NVIDIA GRID K520 GPU.
K80	NVIDIA K80 GPU.
L4	NVIDIA L4 GPU for AI inference and graphics workloads.
L40S	NVIDIA L40S GPU for AI inference and graphics workloads.
M60	NVIDIA M60 GPU.
RADEON_PRO_V520	AMD Radeon Pro V520 GPU.
T4	NVIDIA T4 GPU.
T4G	NVIDIA T4G GPUs.
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.
V100	NVIDIA V100 GPU.
VU9P	Xilinx VU9P FPGA.