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Answered
Hello All, I Installed Self-Hosted Server And Queue(Cosumes 1 Gpu) On Kubernetes. I Have An Issue Regarding Gpu Monitoring. I Checked The Process Is Using Gpu In The Pod, But Gpu Usage Is Not Being Displayed On Workers & Queues Dashboard, Whereas Cpu Usag

Hello all,
I installed self-hosted server and queue(cosumes 1 gpu) on kubernetes.
I have an issue regarding gpu monitoring.
I checked the process is using gpu in the pod, but gpu usage is not being displayed on WORKERS & QUEUES Dashboard, whereas CPU usage is. what is wrong?
image

  
  
Posted one year ago
Votes Newest

Answers 40


because clearml-agnet is not installed in my gke cluster

  
  
Posted one year ago

This is clearml-agent helm chart values.yaml file i used to install

  
  
Posted 12 months ago

@<1523701087100473344:profile|SuccessfulKoala55> I realized that this is not an issue with the cloud or on-premise environment. it’s working well on gke but not working on eks. here is the log when i run “clearml-agent daemon --queue ~” command on eks

root@shelley-gpu-pod:/# clearml-agent daemon --queue shelley3
/usr/local/lib/python3.8/dist-packages/requests/init.py:109: RequestsDependencyWarning: urllib3 (2.0.1) or chardet (None)/charset_normalizer (3.1.0) doesn’t match a supported version!
warnings.warn(
Using environment access key CLEARML_API_ACCESS_KEY=“”
Using environment secret key CLEARML_API_SECRET_KEY=********
Current configuration (clearml_agent v1.5.2, location: None):

agent.worker_id =
agent.worker_name = shelley-gpu-pod
agent.force_git_ssh_protocol = false
agent.python_binary =
agent.package_manager.type = pip
agent.package_manager.pip_version.0 = <20.2 ; python_version < ‘3.10’
agent.package_manager.pip_version.1 = <22.3 ; python_version >= ‘3.10’
agent.package_manager.system_site_packages = false
agent.package_manager.force_upgrade = false
agent.package_manager.conda_channels.0 = pytorch
agent.package_manager.conda_channels.1 = conda-forge
agent.package_manager.conda_channels.2 = defaults
agent.package_manager.priority_optional_packages.0 = pygobject
agent.package_manager.torch_nightly = false
agent.package_manager.poetry_files_from_repo_working_dir = false
agent.venvs_dir = /root/.clearml/venvs-builds
agent.venvs_cache.max_entries = 10
agent.venvs_cache.free_space_threshold_gb = 2.0
agent.venvs_cache.path = ~/.clearml/venvs-cache
agent.vcs_cache.enabled = true
agent.vcs_cache.path = /root/.clearml/vcs-cache
agent.venv_update.enabled = false
agent.pip_download_cache.enabled = true
agent.pip_download_cache.path = /root/.clearml/pip-download-cache
agent.translate_ssh = true
agent.reload_config = false
agent.docker_pip_cache = /root/.clearml/pip-cache
agent.docker_apt_cache = /root/.clearml/apt-cache
agent.docker_force_pull = false
agent.default_docker.image = nvidia/cuda:10.2-cudnn7-runtime-ubuntu18.04
agent.enable_task_env = false
agent.hide_docker_command_env_vars.enabled = true
agent.hide_docker_command_env_vars.parse_embedded_urls = true
agent.abort_callback_max_timeout = 1800
agent.docker_internal_mounts.sdk_cache = /clearml_agent_cache
agent.docker_internal_mounts.apt_cache = /var/cache/apt/archives
agent.docker_internal_mounts.ssh_folder = ~/.ssh
agent.docker_internal_mounts.ssh_ro_folder = /.ssh
agent.docker_internal_mounts.pip_cache = /root/.cache/pip
agent.docker_internal_mounts.poetry_cache = /root/.cache/pypoetry
agent.docker_internal_mounts.vcs_cache = /root/.clearml/vcs-cache
agent.docker_internal_mounts.venv_build = ~/.clearml/venvs-builds
agent.docker_internal_mounts.pip_download = /root/.clearml/pip-download-cache
agent.apply_environment = true
agent.apply_files = true
agent.custom_build_script =
agent.disable_task_docker_override = false
agent.default_python = 3.8
agent.cuda_version = 110
agent.cudnn_version = 0
api.version = 1.5
api.verify_certificate = true
api.default_version = 1.5
api.http.max_req_size = 15728640
api.http.retries.total = 240
api.http.retries.connect = 240
api.http.retries.read = 240
api.http.retries.redirect = 240
api.http.retries.status = 240
api.http.retries.backoff_factor = 1.0
api.http.retries.backoff_max = 120.0
api.http.wait_on_maintenance_forever = true
api.http.pool_maxsize = 512
api.http.pool_connections = 512
api.http.default_method = post
api.api_server = “”
api.files_server = “”
api.web_server = “”
api.credentials.access_key = “”
sdk.storage.cache.default_base_dir = ~/.clearml/cache
sdk.storage.cache.size.min_free_bytes = 10GB
sdk.storage.direct_access.0.url = file://*
sdk.metrics.file_history_size = 100
sdk.metrics.matplotlib_untitled_history_size = 100
sdk.metrics.images.format = JPEG
sdk.metrics.images.quality = 87
sdk.metrics.images.subsampling = 0
sdk.metrics.tensorboard_single_series_per_graph = false
sdk.network.metrics.file_upload_threads = 4
sdk.network.metrics.file_upload_starvation_warning_sec = 120
sdk.network.iteration.max_retries_on_server_error = 5
sdk.network.iteration.retry_backoff_factor_sec = 10
sdk.aws.s3.key =
sdk.aws.s3.region =
sdk.aws.boto3.pool_connections = 512
sdk.aws.boto3.max_multipart_concurrency = 16
sdk.log.null_log_propagate = false
sdk.log.task_log_buffer_capacity = 66
sdk.log.disable_urllib3_info = true
sdk.development.task_reuse_time_window_in_hours = 72.0
sdk.development.vcs_repo_detect_async = true
sdk.development.store_uncommitted_code_diff = true
sdk.development.support_stopping = true
sdk.development.default_output_uri =
sdk.development.force_analyze_entire_repo = false
sdk.development.suppress_update_message = false
sdk.development.detect_with_pip_freeze = false
sdk.development.worker.report_period_sec = 2
sdk.development.worker.ping_period_sec = 30
sdk.development.worker.log_stdout = true
sdk.development.worker.report_global_mem_used = false

Worker “shelley-gpu-pod:gpuGPU-a8a68c42-d19b-c677-5fd3-889bdce415fb” - Listening to queues:
+----------------------------------+----------+-------+
| id | name | tags |
+----------------------------------+----------+-------+
| 1a63b1506e1d4ba4b6ca290a63eceb6b | shelley3 | |
+----------------------------------+----------+-------+

Running CLEARML-AGENT daemon in background mode, writing stdout/stderr to /tmp/.clearml_agent_daemon_outj1su2mo5.txt

  
  
Posted one year ago

is that the working scenario?

  
  
Posted one year ago

You can do that by passing the CLEARML_AGENT_UPDATE_VERSION=1.5.3rc2 env var

  
  
Posted one year ago

@<1523701087100473344:profile|SuccessfulKoala55> Okay..but how can i specify agent’s verison in helm chart?

  
  
Posted one year ago

It looks like the log was truncated - can you please try to get all the log from running the agent in the cloud machine?

  
  
Posted one year ago

but it's running, isn't it?

  
  
Posted one year ago

@<1524922424720625664:profile|TartLeopard58> the agent running the task is v1.5.2 (as shown in the log), so the whole point is lost - we need to see the v1.5.3rc2 or v1.5.3rc3 running there... how did you set up the helm chart for the new agent?

  
  
Posted 12 months ago

Oh, It’s not the issue with eks.. We had the same issue on an on-premise cluster too(clearml-agent is installed). Could it be because of clearml-agent installed?

  
  
Posted one year ago
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40 Answers
one year ago
12 months ago
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