New RunLLM response generated: >>>*# Question* I am having trouble configuring shm (shared memory for the cluster). I have created a “Memory” volume, and also assigned sizeLimit of “20Gi”. The pod description accurately reflects the new tmpfs file system and size. However when I SSH into the container running on the Pod, I see only 4.3Gi allocated. The node has 64GB of RAM. Any pointers, how I can solve this?. Thank you !! # Answer To configure shared memory (

/dev/shm

) for a Flyte task, you need to ensure that the

PodTemplate

is correctly set up and applied to the task. Here is a step-by-step guide based on the provided data sources: 1. Create a PodTemplate: Define a

PodTemplate

with an

emptyDir

volume for shared memory. Ensure the

medium

is set to

"Memory"

and specify the

sizeLimit

. 2. Apply the PodTemplate to the Task: Use the

pod_template

parameter in the

@task

decorator to apply the

PodTemplate

. Here is an example:

from flytekit import task, PodTemplate
from kubernetes.client import V1PodSpec, V1Container, V1Volume, V1VolumeMount, V1EmptyDirVolumeSource

# Define the PodTemplate
gpu_pod_template = PodTemplate(
    primary_container_name="primary",
    pod_spec=V1PodSpec(
        containers=[
            V1Container(
                name="primary",
                volume_mounts=[V1VolumeMount(mount_path="/dev/shm", name="dshm")],
            ),
        ],
        volumes=[
            V1Volume(
                name="dshm",
                empty_dir=V1EmptyDirVolumeSource(medium="Memory", size_limit="20Gi"),
            )
        ],
    ),
)

# Apply the PodTemplate to the task
@task(
    container_image="your_image",
    pod_template=gpu_pod_template,
)
def your_task():
    # Your task logic here
    pass

Note: Ensure that the

size_limit

is correctly set and that the node has sufficient memory available. If you still encounter issues with the allocated shared memory not matching the specified

size_limit

, it might be related to Kubernetes or the underlying node configuration. Double-check the node's available resources and Kubernetes settings. Would you like more detailed steps or further assistance? Sources: - Flyte Discussion on GPU and Shared Memory - Flyte GitHub Issue on Shared Memory Slack Link https://.slack.com/archives/CP2HDHKE1/p1726817398.319169 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.