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2
docs/clearml_agent.md
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@ -233,7 +233,7 @@ clearml-agent daemon --detached --queue default --gpus 1
``` ```
To allocate more than one GPU, provide a list of allocated GPUs To allocate more than one GPU, provide a list of allocated GPUs
```bash ```bash
clearml-agent daemon --gpus 0,1 --queue dual_gpu & clearml-agent daemon --gpus 0,1 --queue dual_gpu
``` ```
#### Queue Prioritization #### Queue Prioritization

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docs/fundamentals/agents_and_queues.md
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@ -100,7 +100,7 @@ available to them. Some tasks are mostly idling and require less computation pow
a pipeline controller) or service tasks (e.g. cleanup service). a pipeline controller) or service tasks (e.g. cleanup service).
This is where the `services-mode` comes into play. An agent running in `services-mode` will let multiple tasks execute This is where the `services-mode` comes into play. An agent running in `services-mode` will let multiple tasks execute
in parallel (each task will register itself as a sub-agent, visible in the [Workers & Queues](../webapp/webapp_workers_queues.md) tab in the UI). in parallel (each task will register itself as a sub-agent, visible in the [Orchestration](../webapp/webapp_workers_queues.md) tab in the UI).
This mode is intended for running maintenance tasks. Some suitable tasks include: This mode is intended for running maintenance tasks. Some suitable tasks include:

2
docs/guides/ide/google_colab.md
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@ -55,7 +55,7 @@ and running, users can send Tasks to be executed on Google Colab's HW.
For additional options for running `clearml-agent`, see the [clearml-agent reference](../../clearml_agent/clearml_agent_ref.md). For additional options for running `clearml-agent`, see the [clearml-agent reference](../../clearml_agent/clearml_agent_ref.md).
After cell 4 is executed, the worker should now appear in the [**Workers & Queues**](../../webapp/webapp_workers_queues.md) After cell 4 is executed, the worker should now appear in the [**Orchestration**](../../webapp/webapp_workers_queues.md)
page of your server. Clone experiments and enqueue them to your hearts content! The `clearml-agent` will fetch page of your server. Clone experiments and enqueue them to your hearts content! The `clearml-agent` will fetch
experiments and execute them using the Google Colab hardware. experiments and execute them using the Google Colab hardware.

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docs/webapp/webapp_home.md
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@ -6,7 +6,8 @@ title: Dashboard
The **Dashboard** provides the following options: The **Dashboard** provides the following options:
* Quickly access the summarized monitoring of recently updated projects and their experiments * Quickly access the summarized monitoring of recently updated projects and their experiments
* Create new projects * Create new projects
* Open the [**Workers & Queues**](webapp_workers_queues.md) tab to monitor resource utilization and to manage queues. * Open the [**Orchestration**](webapp_workers_queues.md) tab to autoscale, monitor, and manage your resource usage and
worker queues.
![Dashboard](../img/webapp_dashboard.png) ![Dashboard](../img/webapp_dashboard.png)
@ -25,10 +26,10 @@ The **Dashboard** provides the following options:
**To create a new project:** **To create a new project:**
1. Click **+ NEW PROJECT** 1. Click **+ NEW PROJECT**
1. Enter the project name, and, optionally, the description and default output destination 1. Enter the project name, and, optionally, the description and default output destination
1. Click **CREATE PROJECT** 1. Click **CREATE PROJECT**
**To monitor resources utilization, and manage queues and workers:** **To autoscale, monitor, and manage your resource usage and workers queues:**
* Click **MANAGE WORKERS AND QUEUES**. The **Workers & Queues** appear. * Click **MANAGE WORKERS AND QUEUES** to go to the [**Orchestration**](webapp_workers_queues.md) page.