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| Partition | Number of nodes | CPU | RAM | Proportional RAM /for 1 CPU | Proportional RAM /for 1 GPU | Proportional CPU/CPUs for 1 GPU | Accelerator |
|---|---|---|---|---|---|---|---|
| plgrid | 532 | 48 cores, Intel(R) Xeon(R) Platinum 8268 CPU @ 2.90GHz | 192GB | 3850MB | n/a | n/a | |
| plgrid-bigmem | 256 | 48 cores, Intel(R) Xeon(R) Platinum 8268 CPU @ 2.90GHz | 384GB | 7700MB | n/a | n/a | |
| plgrid-gpu-v100 | 9 | 32 cores, Intel(R) Xeon(R) Gold 6242 CPU @ 2.80GHz | 384GB | n/a | 46000M | 4 | 8x Tesla V100-SXM2 |
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Resource allocated on Ares doesn't use normalization, which was used on Prometheus and previous clusters. 1 hour of CPU time equals 1 hour spent on a computing core with a proportional amount of memory (consult the table above). The billing system accounts for jobs with more memory than the proportional amount. If the job uses more memory for each allocated CPU than the proportional amount, it will be billed as it would have used more CPUs. The billed amount can be calculated by dividing the used memory used by the proportional memory per core and rounding the result to the closest and larger integer. Jobs on CPU partitions are always billed in CPU hours.
The same principle was applied to GPU resources, where the GPU-hour is a billing unit, and there are proportional memory per GPU and proportional CPUs per GPU defined (consult the table above).
For example, for a typical CPU job if the job uses the propoertional amount of memory per core, or less, then the job is simply billed for the time spent using CPUs. If the job used more memory than the proportional amount, the cost is The cost can be expressed as a simple algorithm:
| Code Block |
|---|
cost_cpu = job_cpus_used * job_duration cost_memory = ceil(job_memory_used/memory_per_cpu) * job_duration final_cost = max(cost_cpu, cost_memory) |
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| Code Block |
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cost_gpu = job_gpus_used * job_duration cost_cpu = ceil(job_cpus_used/cpus_per_gpu) * job_duration cost_memory = ceil(job_memory_used/memory_per_gpu) * job_duration final_cost = max(cost_gpu, cost_cpu, cost_memory) |
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