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All ''general-purpose'' systems are similar with some differences in interconnect and the number of small memory, large memory and GPU nodes. Niagara is a different system and is designed for ''large parallel'' jobs.
A ''general-purpose'' cluster is designed to support a wide variety of types of jobs, and is composed of a mixture of different nodes.  We broadly classify the nodes as:
* ''base'' nodes, containing typically about 4GB of memory per core;
* ''large-memory'' nodes, containing typically more than 8GB memory per core;
* ''GPU'' nodes, which contain [https://en.wikipedia.org/wiki/Graphics_processing_unit graphic processing units].


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The ''large parallel'' cluster [[Niagara]] is designed to support multi-node parallel jobs requiring more than 1000 CPU cores, although jobs as small as a single node are also supported there.  Niagara is composed of nodes of a uniform design, with an interconnect optimized for large jobs.
All systems have large, high-performance attached storage; see the relevant cluster page for more details.


===Types of compute clusters=== <!--T:12-->
All clusters have large, high-performance storage attached.  For details about storage, memory, CPU model and count, GPU model and count, and the number of nodes at each site, please see the individual cluster pages linked under "Resources" at left.
 
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{| class="wikitable"
|-
! Type !! Type of nodes !! Type of jobs
|-
| General-purpose
|
* Small memory nodes
* Regular nodes (4GB/core)
* Large memory nodes
* GPU nodes
|
* Serial and small parallel jobs
* Small or large memory jobs
* GPU jobs
|-
| Large parallel
|
* Uniform nodes (4GB/core)
* Optimized interconnect
|
* Parallel jobs requiring +1000 cores
|}


===List of compute clusters=== <!--T:14-->
===List of compute clusters=== <!--T:14-->

Revision as of 20:08, 1 April 2022

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Compute clusters

A general-purpose cluster is designed to support a wide variety of types of jobs, and is composed of a mixture of different nodes. We broadly classify the nodes as:

  • base nodes, containing typically about 4GB of memory per core;
  • large-memory nodes, containing typically more than 8GB memory per core;
  • GPU nodes, which contain graphic processing units.

The large parallel cluster Niagara is designed to support multi-node parallel jobs requiring more than 1000 CPU cores, although jobs as small as a single node are also supported there. Niagara is composed of nodes of a uniform design, with an interconnect optimized for large jobs.

All clusters have large, high-performance storage attached. For details about storage, memory, CPU model and count, GPU model and count, and the number of nodes at each site, please see the individual cluster pages linked under "Resources" at left.

List of compute clusters

Name and link Type Sub-systems Status
Béluga General-purpose
  • beluga-compute
  • beluga-gpu
  • beluga-storage
In production
Cedar General-purpose
  • cedar-compute
  • cedar-gpu
  • cedar-storage
In production
Graham General-purpose
  • graham-compute
  • graham-gpu
  • graham-storage
In production
Narval General-purpose
  • narval-compute
  • narval-gpu
  • narval-storage
In production
Niagara Large parallel
  • niagara-compute
  • niagara-storage
  • hpss-storage
In production

Cloud - Infrastructure as a Service

Our cloud systems are offering an Infrastructure as a Service (IaaS) based on OpenStack.

Name and link Sub-systems Description Status
Arbutus cloud
  • arbutus-compute-cloud
  • arbutus-persistent-cloud
  • arbutus-dcache
  • VCPU, VGPU, RAM
  • Local ephemeral disk
  • Volume and snapshot storage
  • Shared filesystem storage (backed up)
  • Object storage
  • Floating IPs
  • dCache storage
In production
Béluga cloud
  • beluga-compute-cloud
  • beluga-persistent-cloud
  • VCPU, RAM
  • Local ephemeral disk
  • Volume and snapshot storage
  • Floating IPs
In production
Cedar cloud
  • cedar-persistent-cloud
  • cedar-compute-cloud
  • VCPU, RAM
  • Local ephemeral disk
  • Volume and snapshot storage
  • Floating IPs
In production
Graham cloud
  • graham-persistent-cloud
  • VCPU, RAM
  • Local ephemeral disk
  • Volume and snapshot storage
  • Floating IPs
In production