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    # Resource Accounting Policy
    
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    Starting with the 24<sup>th</sup> open access grant competition, the accounting policy has been changed from [normalized core hours (NCH)][2a] to **node-hours**. This means that it is now required to apply for node hours of the specific cluster and node type:
    
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    1. [Barbora CPU][3a]
    
    1. [Barbora GPU][4a]
    
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    1. [Barbora FAT][5a]
    1. [DGX-2][6a]
    1. [Karolina CPU][7a]
    1. [Karolina GPU][8a]
    1. [Karolina FAT][9a]
    
    
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    The accounting runs whenever the nodes are allocated via the PBS Pro workload manager (the `qsub` command), regardless of whether
    the nodes are actually used for any calculation. The same rule applies for unspent [reservations][10a].
    
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    ## Conversion Table
    
    
    | Resources | Conversion for 1 node-hour |
    
    | ------------ | ----------------------- |
    
    | Barbora CPU  | 36 core-hours           |
    | Barbora GPU  | 4 GPU core-hours        |
    | Barbora FAT  | 128 core-hours          |
    | DGX-2        | 16 GPU core-hours       |
    | Karolina CPU | 128 core-hours          |
    | Karolina GPU | 8 GPU core-hours        |
    | Karolina FAT | 768 core-hours          |
    
    
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    ## Original Resource Accounting Policy
    
    The original policy, as stated below, is still applied to projects from previous grant competitions.
    
    
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    ### Wall-Clock Core-Hours WCH
    
    The wall-clock core-hours (WCH) are the basic metric of computer utilization time.
    
    1 wall-clock core-hour is defined as 1 processor core allocated for 1 hour of wall-clock time. For example, allocating a full node (i.e. 36 cores) on Barbora for 1 hour amounts to 36 wall-clock core-hours.
    
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    ### Normalized Core-Hours NCH
    
    The resources subject to accounting are the normalized core-hours (NCH).
    The normalized core-hours are obtained from WCH by applying a normalization factor:
    
    $$
    NCH = F*WCH
    $$
    
    All jobs are accounted in normalized core-hours, using factor F valid at the time of the execution:
    
    
    | System        | F    |
    | --------------| ---: |
    | Karolina      | 1.00 |
    | Barbora CPU   | 1.40 |
    | Barbora GPU   | 4.50 |
    | DGX-2         | 5.50 |
    
    Factors are valid as of July 9, 2022.
    
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    The normalized core-hours were introduced to treat systems of different age on equal footing.
    
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    Normalized core-hour is an accounting tool to discount the legacy systems.
    
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    See examples in the [Job submission and execution][1a] section.
    
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    ### Consumed Resources
    
    
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    Check how many core-hours have been consumed. The command `it4ifree` is available on cluster login nodes.
    
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    ```console
    $ it4ifree
    
    Projects I am participating in
    ==============================
    PID         Days left      Total    Used WCHs    Used NCHs    WCHs by me    NCHs by me     Free
    ----------  -----------  -------  -----------  -----------  ------------  ------------  -------
    OPEN-XX-XX  323                0      5169947      5169947         50001         50001  1292555
    
    
    Projects I am Primarily Investigating
    =====================================
    PID        Login         Used WCHs    Used NCHs
    ---------- ----------  -----------  -----------
    OPEN-XX-XX user1            376670       376670
               user2           4793277      4793277
    
    Legend
    ======
    WCH   =    Wall-clock Core Hour
    NCH   =    Normalized Core Hour
    ```
    
    The `it4ifree` command is a part of the `it4i.portal.clients` package, located [here][pypi].
    
    
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    [1a]: job-submission-and-execution.md
    [2a]: #normalized-core-hours-nch
    [3a]: ../../barbora/compute-nodes/#compute-nodes-without-accelerators
    [4a]: ../../barbora/compute-nodes/#compute-nodes-with-a-gpu-accelerator
    [5a]: ../../barbora/compute-nodes/#fat-compute-node
    [6a]: ../../dgx2/introduction/
    [7a]: ../../karolina/compute-nodes/#compute-nodes-without-accelerators
    [8a]: ../../karolina/compute-nodes/#compute-nodes-with-a-gpu-accelerator
    [9a]: ../../karolina/compute-nodes/#data-analytics-compute-node
    
    [10a]: resource_allocation_and_job_execution.md#resource-reservation
    
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    [pypi]: https://pypi.python.org/pypi/it4i.portal.clients