Difference between revisions of "Quickstart/What Is Viper"

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(Vipers' hardware)
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== Vipers' hardware ==
 
== Vipers' hardware ==
  
Viper is based on the Linux operating system and is composed of approximately 5,500 processing cores with the following specialised areas:
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{| class="wikitable mw-collapsible "
* 180 compute nodes, each with 2x 14-core Intel Broadwell E5-2680v4 processors (2.4 –3.3 GHz), 128 GB DDR4 RAM
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| style="width:25%; background: #ecc;" | Hardware
* 4 High memory nodes, each with 4x 10-core Intel Haswell E5-4620v3 processors (2.0 GHz), 1TB DDR4 RAM
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| style="width:75%;background: #ecc; " |
* 4 GPU nodes, each identical to compute nodes with the addition of a Nvidia Ampere A40 GPU per node
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|-
* 2 Visualisations nodes with 2x Nvidia GTX 980TI
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|[[File: Computenodes.jpg]]
* Intel [http://www.intel.com/content/www/us/en/high-performance-computing-fabrics/omni-path-architecture-fabric-overview.html Omni-Path] interconnect (100 Gb/s node-switch and switch-switch)
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|  '''Compute Nodes'''<br>These make up most of the computing nodes and perform most of the standard computing processes within the HPC. Each node has 128GByte of RAM.
* 500 TB parallel file system ([http://www.beegfs.com/ BeeGFS])
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|-
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|[[File: Highmemorynodes.jpg]]
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| '''High Memory Nodes'''<br>These are very similar to the compute nodes but they have much more memory, ours have a 1 Tera Byte of RAM each which makes them ideal for research involving large memory models like engineering and DNA analysis in biology.
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|-
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|[[File:Acceleratornodes.jpg]]
 +
|'''Accelerator Nodes'''<br>Also known as GPU nodes. We have 4 GPU nodes, each identical to compute nodes with the addition of an Nvidia Ampere A40 GPU per node. These are almost similar to high-end graphics cards found in gaming rigs. The usefulness of these cards is that they have thousands of very small processing cores in them and this makes them very useful for executing small amounts of code but in a massively parallel way. This is why these cards are used for the new areas of machine learning and deep learning also.
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|-
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|[[File: Visualisationnodes.jpg]]
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|'''Visualisation Nodes'''<br>These are used for connecting from remote computers such as desktops and allow the rendered outputs from data to be viewed on a local computer. There are two visualisations nodes with 2x Nvidia GTX 980TI.
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|-
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|[[File: Highspeednetwork.jpg]]
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|'''High Speed Network'''<br>All these compute nodes are connected by a very fast Intel Omni-path network to allow the compute nodes to act together. This runs at 100Gbit/s.
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|-
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|[[File: Storagenodes.jpg]]
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|'''Storage Nodes'''<br>These are servers in their own right which allow access to the actual storage arrays (hard disks), Viper accesses it’s disk storage via these nodes.
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|-
 +
|[[File: Storagearray.jpg]]
 +
|'''Storage Array'''<br>These are the actual disks held in a chassis and make up the whole file storage for Viper. Viper has a total file space of 0.5 Petabyte or 500 Terabyte.
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|-
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|[[File:Controllernodes.jpg]]
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|'''Controller Node'''<br>The controller nodes are responsible for the management of all the compute nodes. Managing the loading of jobs, their termination and completion via the job scheduler, for Viper this is SLURM.
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|-
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|[[ File:Loginnodes.jpg ]]
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|'''Login Nodes'''These are the nodes which allow the user to log in to the cluster, this area is then used by the user to prepare jobs for the cluster. Although this is a server in its own right it is not used for computing work.
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|-
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|}
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Revision as of 11:05, 8 November 2022

What is Viper?

Viper is the University of Hull's supercomputer and is located on-site with its own dedicated team to administrate it and develop applications upon it.

What is a supercomputer?

A supercomputer is a computer with a high level of computing performance compared to a general-purpose computer. It achieves this level of performance by allowing the user to split a large job into smaller computation tasks which then run in parallel, or by running a single task with many different scenarios on the data across parallel processing units.

Why do we need a supercomputer?

The point of having a high-performance computer is so that the individual nodes can work together to solve a problem larger than any one computer can easily solve. And, just like people, the nodes need to be able to talk to one another in order to work meaningfully together. Of course, computers talk to each other over networks, and there is a variety of computer network (or interconnect) options available for business clusters (see here for an overview of cluster interconnects).

Supercomputers generally aim for the maximum in capability computing rather than capacity computing. Capability computing is typically thought of as using the maximum computing power to solve a single large problem in the shortest amount of time. Often a capability system is able to solve a problem of a size or complexity that no other computer can, e.g., a very complex weather simulation application.

How does a supercomputer work?

A high-performance computer like Viper has a lot of elements of a desktop computer — processors, memory, disk, operating system — just more of them. High-performance computers split off some of the tasks into separate elements to gain performance. An example of this on Viper is how it handles disk storage, which is a separate server with all of the storage directly connected to it. This is then connected across a high-speed network to all other individual computers (referred to as nodes).

Like just about all other supercomputers Viper runs on Linux, which is similar to UNIX in many ways and has a wide body of software to support it.

How powerful is Viper?

Viper's real compute power is achieved by having a large amount of standard compute nodes (Compute), in our case 180 of them. Each of those nodes has 28 processing cores, so a total of 5040 processing cores ( i.e. 180 x 28 cores ). Some specialised nodes are included which are more suited to dedicated applications, such as high memory (Highmem) nodes and GPU accelerator (GPU) nodes which are particularly suited to large memory modelling and machine learning respectively.

What is Viper used for?

The uses of supercomputers are widespread and continue to be used in new and novel ways every day.

Viper is used for

  • Astrophysics
  • BioEngineering
  • Business School
  • Chemistry
  • Computer Science
  • Computation Linguistics
  • Geography
  • And many more


Vipers' hardware

Hardware
Computenodes.jpg Compute Nodes
These make up most of the computing nodes and perform most of the standard computing processes within the HPC. Each node has 128GByte of RAM.
Highmemorynodes.jpg High Memory Nodes
These are very similar to the compute nodes but they have much more memory, ours have a 1 Tera Byte of RAM each which makes them ideal for research involving large memory models like engineering and DNA analysis in biology.
Acceleratornodes.jpg Accelerator Nodes
Also known as GPU nodes. We have 4 GPU nodes, each identical to compute nodes with the addition of an Nvidia Ampere A40 GPU per node. These are almost similar to high-end graphics cards found in gaming rigs. The usefulness of these cards is that they have thousands of very small processing cores in them and this makes them very useful for executing small amounts of code but in a massively parallel way. This is why these cards are used for the new areas of machine learning and deep learning also.
Visualisationnodes.jpg Visualisation Nodes
These are used for connecting from remote computers such as desktops and allow the rendered outputs from data to be viewed on a local computer. There are two visualisations nodes with 2x Nvidia GTX 980TI.
Highspeednetwork.jpg High Speed Network
All these compute nodes are connected by a very fast Intel Omni-path network to allow the compute nodes to act together. This runs at 100Gbit/s.
Storagenodes.jpg Storage Nodes
These are servers in their own right which allow access to the actual storage arrays (hard disks), Viper accesses it’s disk storage via these nodes.
Storagearray.jpg Storage Array
These are the actual disks held in a chassis and make up the whole file storage for Viper. Viper has a total file space of 0.5 Petabyte or 500 Terabyte.
Controllernodes.jpg Controller Node
The controller nodes are responsible for the management of all the compute nodes. Managing the loading of jobs, their termination and completion via the job scheduler, for Viper this is SLURM.
Loginnodes.jpg Login NodesThese are the nodes which allow the user to log in to the cluster, this area is then used by the user to prepare jobs for the cluster. Although this is a server in its own right it is not used for computing work.




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