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ResourceRequirement - AWS Batch
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ResourceRequirement

The type and amount of a resource to assign to a container. The supported resources include GPU, MEMORY, and VCPU.

Contents

type

The type of resource to assign to a container. The supported resources include GPU, MEMORY, and VCPU.

Type: String

Valid Values: GPU | VCPU | MEMORY

Required: Yes

value

The quantity of the specified resource to reserve for the container. The values vary based on the type specified.

type="GPU"

The number of physical GPUs to reserve for the container. Make sure that the number of GPUs reserved for all containers in a job doesn't exceed the number of available GPUs on the compute resource that the job is launched on.

Note

GPUs aren't available for jobs that are running on Fargate resources.

type="MEMORY"

The memory hard limit (in MiB) present to the container. This parameter is supported for jobs that are running on Amazon EC2 resources. If your container attempts to exceed the memory specified, the container is terminated. This parameter maps to Memory in the Create a container section of the Docker Remote API and the --memory option to docker run. You must specify at least 4 MiB of memory for a job. This is required but can be specified in several places for multi-node parallel (MNP) jobs. It must be specified for each node at least once. This parameter maps to Memory in the Create a container section of the Docker Remote API and the --memory option to docker run.

Note

If you're trying to maximize your resource utilization by providing your jobs as much memory as possible for a particular instance type, see Memory management in the AWS Batch User Guide.

For jobs that are running on Fargate resources, then value is the hard limit (in MiB), and must match one of the supported values and the VCPU values must be one of the values supported for that memory value.

value = 512

VCPU = 0.25

value = 1024

VCPU = 0.25 or 0.5

value = 2048

VCPU = 0.25, 0.5, or 1

value = 3072

VCPU = 0.5, or 1

value = 4096

VCPU = 0.5, 1, or 2

value = 5120, 6144, or 7168

VCPU = 1 or 2

value = 8192

VCPU = 1, 2, or 4

value = 9216, 10240, 11264, 12288, 13312, 14336, or 15360

VCPU = 2 or 4

value = 16384

VCPU = 2, 4, or 8

value = 17408, 18432, 19456, 21504, 22528, 23552, 25600, 26624, 27648, 29696, or 30720

VCPU = 4

value = 20480, 24576, or 28672

VCPU = 4 or 8

value = 36864, 45056, 53248, or 61440

VCPU = 8

value = 32768, 40960, 49152, or 57344

VCPU = 8 or 16

value = 65536, 73728, 81920, 90112, 98304, 106496, 114688, or 122880

VCPU = 16

type="VCPU"

The number of vCPUs reserved for the container. This parameter maps to CpuShares in the Create a container section of the Docker Remote API and the --cpu-shares option to docker run. Each vCPU is equivalent to 1,024 CPU shares. For Amazon EC2 resources, you must specify at least one vCPU. This is required but can be specified in several places; it must be specified for each node at least once.

The default for the Fargate On-Demand vCPU resource count quota is 6 vCPUs. For more information about Fargate quotas, see AWS Fargate quotas in the AWS General Reference.

For jobs that are running on Fargate resources, then value must match one of the supported values and the MEMORY values must be one of the values supported for that VCPU value. The supported values are 0.25, 0.5, 1, 2, 4, 8, and 16

value = 0.25

MEMORY = 512, 1024, or 2048

value = 0.5

MEMORY = 1024, 2048, 3072, or 4096

value = 1

MEMORY = 2048, 3072, 4096, 5120, 6144, 7168, or 8192

value = 2

MEMORY = 4096, 5120, 6144, 7168, 8192, 9216, 10240, 11264, 12288, 13312, 14336, 15360, or 16384

value = 4

MEMORY = 8192, 9216, 10240, 11264, 12288, 13312, 14336, 15360, 16384, 17408, 18432, 19456, 20480, 21504, 22528, 23552, 24576, 25600, 26624, 27648, 28672, 29696, or 30720

value = 8

MEMORY = 16384, 20480, 24576, 28672, 32768, 36864, 40960, 45056, 49152, 53248, 57344, or 61440

value = 16

MEMORY = 32768, 40960, 49152, 57344, 65536, 73728, 81920, 90112, 98304, 106496, 114688, or 122880

Type: String

Required: Yes

See Also

For more information about using this API in one of the language-specific AWS SDKs, see the following:

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