This document is relevant for: Inf1
, Inf2
, Trn1
, Trn2
Neuron Containers FAQ#
Where can I find DLC images#
The Inference/Training DLC images can be found here.
In the DLC release page do a search for neuron to get the ECR repo location of specific neuron DLC release.
What is OCI Neuron Hook and do we need that#
Neuron devices are exposed to the containers using the –device option in the docker run command. Docker runtime (runc) does not yet support the ALL option to expose all neuron devices to the container.
With OCI neuron hook support is added to expose ALL devices to container using an environment variable, “AWS_NEURON_VISIBLE_DEVICES=ALL”. For more details please refer oci neuron hook
In Kubernetes, if we are using the device plugin version 1.7 & below, then the oci neuron hook is needed. If using device plugin version >= 1.8 then oci neuron hook is not needed
What container runtimes are supported#
Neuron containers have been tested to work with docker, containerd, cri-o runtimes without any changes. If the oci neuron hook is used then they need to be enabled in the runtime config. For more details please refer oci neuron hook
How to expose Neuron Devices to Container#
Neuron Device: Represents the number of Inferentia/Trainium chips in the instance. Refer Container Devices for more details
How to expose Neuron Cores to Container#
Neuron Core: Represents the number of Neuron Cores in the instance. Refer Container Cores for more details. Each Inferentia1 device has 4 Neuron Cores and each Inferentia2 and Trainium1 device has 2 Neuron Cores. When the devices are exposed to the containers all the cores in the device are available for use in the container. Please refer NeuronX Runtime Configuration to see how the environment variables NEURON_RT_VISIBLE_CORES and NEURON_RT_NUM_CORES can be used to assign core to containers
When would you use Neuron K8 Scheduler Extension#
The neuron cores/devices that are exposed to the container needs to be contiguous. The kubernetes device plugin does not guarantee the devices to be contiguous. The K8 Neuron Scheduler Extension takes care of assigning contiguous devices to the containers.
How to add EFA devices to the container#
The EFA devices are exposed to the container using the –device option
--device /dev/infiniband/uverbs0
In a Kubernetes environment, the EFA device plugin is used to detect and advertise the available EFA interfaces. The EFA device plugin can be installed using the Helm chart provided by Amazon EKS
helm repo add eks https://aws.github.io/eks-charts
helm install aws-efa-k8s-device-plugin --namespace kube-system eks/aws-efa-k8s-device-plugin
Once the plugin is deployed, applications can use the resource type vpc.amazonaws.com/efa in a pod request spec
resources:
limits:
vpc.amazonaws.com/efa: 4
Can distributed training jobs be run without EFA devices in container#
No. For distributed training jobs on Trainium, all EFA interfaces provided by trn1.32xlarge need to be attached to the container
This document is relevant for: Inf1
, Inf2
, Trn1
, Trn2