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This page provides documentation for all of SHARCNET's computational resources. This includes both hardware specifications as well as specialized usage information as appropriate, and links to information in the web portal.

Which system should I use?

Conventional HPC computing should be done on the core systems based on the particular memory and scaling requirements for the given program. Here is the snapshot with major systems in SHARCNET.

Whichsystem2.png

As a rough suggestion:

  • serial programs should be run on kraken
Serialfarm.png
  • threaded programs (shared-memory) should run on saw, kraken or possibly orca, if they can scale well
  • mpi programs (distributed-memory) should run on requin, saw or orca
Parallel.png
  • large memory jobs can be run in orca (note: hound system is no longer available)
Largememory2.png
  • the MPI jobs needs to run with high network bandwidth may got all core systems
Highnetwork2.png


  • the jobs require high disk I/O may go to orca/saw/requin.
Highdiskio.png

If one has special computing needs (acceleration, visualization, storage, etc.) please see the specialty systems.

There are also a wide array of contributed systems where one may find their jobs run faster than on the core systems and users are invited to try them as well, though they are subject to availability depending on the system's particular scheduling arrangement with the contributor.

Core Systems

This table indicates the primary intent of the system and includes a comparison of common system specifications in terms of their relative performance.

The legend is as follows:

Best Good Okay Poor
Core Systems Target Utilization core/node CPU clock Hz FLOPS/cycle MEM Size/node MEM Bandwidth/socket Cache Size/node Interconnect Parallel
kraken throughput cluster
orca large MPI capacity cluster
requin capability cluster
saw large MPI capacity cluster

Speciality Systems

GPU accelerated Systems

Angel and monk are the Graphic Processing Unit systems. Please check its own page for further information.

Training/Experimentation

mako development/experimental cluster

Storage Systems

Please check Storage_systems.

Visualization

Visualization Workstations Graphical programs

Contributed Systems

Specialty Systems Target Utilization
brown compute cluster
goblin compute cluster
guppy compute cluster
iqaluk SMP system, fast storage
redfin large-memory compute cluster
wobbie compute cluster

How long will my job wait in the queue before it starts to run?

Please see the Current wait time distribution page to see how long various jobs of different sizes have taken to run on each of the core systems. Depending on how busy the systems are you may want to avoid them if you are looking for the fastest time to results.

One can also find important statistics about jobs being scheduled on the clusters in the web portal cluster performance page.