Getting started/en: Difference between revisions

Updating to match new version of source page
(Updating to match new version of source page)
(Updating to match new version of source page)
Line 39: Line 39:
[[Cedar]] (GP2) and [[Graham]] (GP3) are general purpose clusters composed of a variety of nodes including large memory nodes and nodes with accelerators. They went into service in the summer of 2017. You can log in to either one using [[SSH]] and the same password you use at ccdb.computecanada.ca. A home directory will be automatically created for you the first time you log in.   
[[Cedar]] (GP2) and [[Graham]] (GP3) are general purpose clusters composed of a variety of nodes including large memory nodes and nodes with accelerators. They went into service in the summer of 2017. You can log in to either one using [[SSH]] and the same password you use at ccdb.computecanada.ca. A home directory will be automatically created for you the first time you log in.   


[[Niagara]] (LP) will be a large parallel cluster with nodes interconnected by a fast network planned to enter service in early 2018.
[[Niagara]] (LP) is a homogeneous cluster designed for large parallel jobs (>1000 cores). It entered service in March 2018.


Your '''password''' to log in to all new national systems are the same one you use to log in to [https://ccdb.computecanada.ca/ ccdb.computecanada.ca]. Your '''username''' will be displayed at the top of your home page at [https://ccdb.computecanada.ca/ ccdb.computecanada.ca] once you've logged in there.
Your '''password''' to log in to all new national systems are the same one you use to log in to [https://ccdb.computecanada.ca/ ccdb.computecanada.ca]. Your '''username''' will be displayed at the top of your home page at [https://ccdb.computecanada.ca/ ccdb.computecanada.ca] once you've logged in there.
Line 48: Line 48:
Most legacy clusters are classified as either capacity clusters or capability clusters. ''Capacity clusters'' contain nodes connected to each other by a relatively slow Ethernet network, while the ''capability clusters'' have a fast network, usually InfiniBand. Large parallel jobs will run better on capability clusters than capacity clusters, while smaller jobs will run almost anywhere.  
Most legacy clusters are classified as either capacity clusters or capability clusters. ''Capacity clusters'' contain nodes connected to each other by a relatively slow Ethernet network, while the ''capability clusters'' have a fast network, usually InfiniBand. Large parallel jobs will run better on capability clusters than capacity clusters, while smaller jobs will run almost anywhere.  


There are some specialty clusters among the legacy resources. Applications which require more than 512 GB of memory per node require ''large shared memory systems''. Compute Canada has four such systems:
There are a few legacy clusters equipped with accelerators such as [https://en.wikipedia.org/wiki/General-purpose_computing_on_graphics_processing_units GPUs] and Intel [https://en.wikipedia.org/wiki/Xeon_Phi Xeon Phis]. You will find them on the following legacy systems:
* Hungabee hosted by WestGrid
* Helios and Guillimin, hosted by Calcul Québec
* M9000 hosted by the Centre for Advanced Computing
* Guillimin-ScaleMP hosted by Calcul Québec
* Iqaluk, Wobbie, Mosaic hosted by SHARCNET
 
Compute Canada also has clusters equipped with accelerators such as [https://en.wikipedia.org/wiki/General-purpose_computing_on_graphics_processing_units GPUs] and Intel [https://en.wikipedia.org/wiki/Xeon_Phi Xeon Phis]. If your application calls for from such accelerators, in addition to the new systems, you will find them on the following legacy systems:
* Helios, Hades and Guillimin, hosted by Calcul Québec
* Parallel, hosted by WestGrid
* Monk, hosted by SHARCNET
* Accelerator Research Cluster, hosted by SciNet
* Accelerator Research Cluster, hosted by SciNet
All of these have NVidia GPUs. Guillimin also has Intel Xeon Phis.  
All of these have NVidia GPUs. Guillimin also has Intel Xeon Phis.


==What resources should I use?==
==What resources should I use?==
38,760

edits