Fee Structure @ Frontenac
Frontenac serves as our main compute cluster and is operated through the SLURM scheduler. Until March 31, allocations from the 2018 Resource Allocation Competition of Compute Canada, are running on this cluster. The cluster is not among the allocatable systems for the 2019 Compute Canada allocation round ("RAC2019"). Therefore, the operation of Frontenac will be on a cost-recovery basis from April 1, 2019. This page provides details about the fee structure.
The following lists the basic charges for compute and storage usage on the Frontenac cluster. These are meant as a reference to facilitate the decision of whether to continue to use the Frontenac cluster or seek alternatives.
|Compute (CPU usage, High-Priority or Metered)||$XXX/cyr|
|Compute (CPU usage, special arrangements)||Contact us|
|Storage (special arrangements)||Contact us|
Compute and Storage
The new fee structure for the Frontenac Compute cluster applies both to the usage of CPU's and for storage on disk and tape. The fees are raised per annum basis, but can be pro-rated to a shorter duration without penalty. The standard units are :
|CPU usage||core-year (cyr)||
|GPU usage||gpu-year (gyr)||
"High-priority" and "Metered" Compute Access
There are two standard types of access to the Frontenac cluster": "High-Priority" access which provides scheduled access to the cluster which will in most cases be "rapid" for smaller jobs, and "Metered" access which uses a standard priority that may entail longer waiting times but will only be charged according to actual usage. In addition we offer special arrangements. Here is a more detailed explanation:
Project and Nearline storage
There are two standard types of storage on the Frontenac file system, both part of the "Hierarchical Storage Management" system. "Project" storage refers to storage immediately accessible on a disk through the GPFS file system. "Nearline" storage refers to data that reside mostly on tape, but are accessible through disk when needed, albeit with a delay in the case of larger amounts of data being accessed. Here is a more detailed explanation: