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        <title>hpc documentation - abstract:darwin:runjobs</title>
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            <title>accounting</title>
            <link>https://docs-archive.hpc.udel.edu/abstract/darwin/runjobs/accounting</link>
            <description>Job Accounting on DARWIN

Accounting for jobs on DARWIN varies with the type of node used within a given allocation type.  There are two types of allocations:

	*  Compute - for CPU based nodes with 512 GiB, 1024 GiB, or 2048 GiB of RAM
	*  GPU - for GPU based nodes with NVIDIA Tesla T4, NVIDIA Tesla V100, or AMD Radeon Instinct MI50 GPUs</description>
            <author>anonymous@undisclosed.example.com (Anonymous)</author>
            <pubDate>Tue, 24 Mar 2026 16:54:09 +0000</pubDate>
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        <item>
            <title>job_status</title>
            <link>https://docs-archive.hpc.udel.edu/abstract/darwin/runjobs/job_status</link>
            <description>Managing Jobs on DARWIN

Once a user has been able to submit jobs to the cluster -- interactive or batch -- the user will from time to time want to know what those jobs are doing.  Is the job waiting in a queue for resources to become available, or is it executing?  How long has the job been executing? How much CPU time or memory has the job consumed?  Users can query Slurm for job information using the</description>
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            <pubDate>Mon, 18 Aug 2025 20:54:37 +0000</pubDate>
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        <item>
            <title>queues</title>
            <link>https://docs-archive.hpc.udel.edu/abstract/darwin/runjobs/queues</link>
            <description>The job queues (partitions) on DARWIN

The DARWIN cluster has several partitions (queues) available to specify when running jobs.  These partitions correspond to the various node types available in the cluster:
Partition NameDescriptionNode Namesstandard</description>
            <author>anonymous@undisclosed.example.com (Anonymous)</author>
            <pubDate>Tue, 01 Apr 2025 16:08:42 +0000</pubDate>
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            <title>runjobs</title>
            <link>https://docs-archive.hpc.udel.edu/abstract/darwin/runjobs/runjobs</link>
            <description>Running applications on DARWIN

Introduction

The Slurm workload manager (job scheduling system) is used to manage and control the resources available to computational tasks.  The job scheduler considers each job&#039;s resource requests (memory, disk space, processor cores) and executes it as those resources become available.  As a cluster workload manager, Slurm has three key functions: (1) It allocates exclusive and/or non-exclusive access to resources (compute nodes) to users for some duration of…</description>
            <author>anonymous@undisclosed.example.com (Anonymous)</author>
            <pubDate>Fri, 03 Jun 2022 16:53:18 +0000</pubDate>
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        <item>
            <title>schedule_jobs</title>
            <link>https://docs-archive.hpc.udel.edu/abstract/darwin/runjobs/schedule_jobs</link>
            <description>Scheduling Jobs on DARWIN

In order to schedule any job (interactively or batch) on a cluster, you must set your allocation workgroup to define your allocation group and explicitly specify a single partition that corresponds to the compute resources granted for the allocation. For example,&lt;span style=&quot;color:#ffffff;background-color:#2fa4e7;padding:3px 7px !important;border-radius:4px;&quot;&gt;sidebar&lt;/span&gt;</description>
            <author>anonymous@undisclosed.example.com (Anonymous)</author>
            <pubDate>Fri, 30 Jan 2026 01:16:34 +0000</pubDate>
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            <title>sidebar</title>
            <link>https://docs-archive.hpc.udel.edu/abstract/darwin/runjobs/sidebar</link>
            <description>*  Home
	*  Caviness
	*  DARWIN
				*  Request Account
				*  Connecting
				*  Storage
				*  Transfer Files
				*  Application Development
				*  Install Software
				*  Run Jobs
					*  Accounting
					*  Queues
					*  Schedule Jobs 
					*  Managing Jobs

				*  System Status
				*  Security

	*  Farber (Retired)
	*  Mills (Retired)
	*  Software
	*  Training
	*  Technical</description>
            <author>anonymous@undisclosed.example.com (Anonymous)</author>
            <pubDate>Thu, 16 Mar 2023 14:58:03 +0000</pubDate>
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