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
, andVCPU
.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 containersection 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 containersection 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 Amazon 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 theVCPU
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 containersection 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 Amazon Fargate quotas in the Amazon General Reference.
For jobs that are running on Fargate resources, then
value
must match one of the supported values and theMEMORY
values must be one of the values supported for thatVCPU
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 Amazon SDKs, see the following: