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HPRC:AMS:Service Unit

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AMS Service Unit

A 'Service Unit' (SU) is charged to a job when the job uses one 'effective_core' for one hour (walltime).

The calculation of effective_core depends on whether a job is a exclusive job or not ('-x' specified or not).

Exclusive Job

When an exclusive job runs on a node with m cores.
'effective_core = m'
Note that the effective_core for an exclusive job on a node is independent how many cores are requested by the job.

Once the effective_core on a node is calculated, the effective_core for the job is simply the sum of the effective_core on all nodes where the job runs.

Non-Exclusive Job

The effective core on a node are calculated by considering requested memory. When a job requests xxx memory by "-M xxx" (for our LSF configuration on Ada for a node with m cores, this is the runtime memory limit per core) and yyy cores by "-n yyy), thenfor that requested memory, we have
'memory_equivalent_core = min(m, ceil(xxx*yyy/total_memory*m))'
where total_memory is the total memory on a node available to users.

Example 1

   A nxt node has 20 cores and around 50G memory available to users. 
   When a job requests 2.5G memory and 2 cores, the job uses memory_equivalent_core of min(20, ceil(2.5*2/50*20))=2 core. 

Example 2

   A nxt node has 20 cores and around 50G memory available to users. 
   When the job requests 3G memory and 2 cores, the job uses memory_equivalent_core of min(20, ceil(3*2/50*20))=3 cores.

Example 3

   A nxt node has 20 cores and around 50G memory available to users. 
   When the job requests 8G memoryand 10 cores, the job uses memory_equivalent_core of min(20, ceil(8*10/50*20))=20 cores.

Once the memory_equivalent_core is calculated, the effective_core on a node where a job request yyy cores can be calculated as below:

  effective_core = max(yyy, memory_equivalent_cores)

Finally, the effective_core for a job is the sum of the effective_core on all nodes where the job runs.

SUs for Jobs Requesting GPUs

On Terra, a job requesting GPUs is considered as an exclusive job. That is, the SUs consumed by the job is calculated based on all CPUs on GPU nodes. For example, if a job requests one CPU and a GPU, then the job is a GPU job. The SUs for the GPU job is calculated as for 28 CPUs (all CPUs on a GPU node).