Cluster Info - Revision history

Rmh325 at 04:46, 21 December 2022

2022-12-21T04:46:23Z

Rmh325 at 17:17, 18 November 2022

2022-11-18T17:17:33Z

Rmh325 at 16:58, 7 October 2022

2022-10-07T16:58:32Z

Admin at 04:11, 28 September 2022

2022-09-28T04:11:37Z

Admin: /* Math Cluster */

2022-09-28T04:05:59Z

Math Cluster

Admin at 16:37, 24 September 2022

2022-09-24T16:37:34Z

Admin at 20:28, 25 July 2022

2022-07-25T20:28:17Z

Admin at 14:57, 21 July 2022

2022-07-21T14:57:26Z

Admin: Created page with " == Math Cluster == The Math Department has an experimental computational cluster. It works fine for computation, but the main purpose is for configuring and testing distribut..."

2022-07-21T14:27:51Z

Created page with " == Math Cluster == The Math Department has an experimental computational cluster. It works fine for computation, but the main purpose is for configuring and testing distribut..."

New page

== Math Cluster ==
The Math Department has an experimental computational cluster. It works fine for computation, but the main purpose is for configuring and testing distributed computing applications so that they can be run on larger clusters.

The cluster is 40 machines with i7 processors. The first 32 are 6th-generation processors, and the last 8 are 7th generation processors.

Jobs can be sent to all nodes in the cluster, or a subset of the nodes.

At this time, the cluster is working with ssh and Mathematica. We're in the process of getting it working with other applications including MPI, Matlab, Maple, and Magma. Check back on this page because support is rapidly evolving.

Also, if you can get your own application running on the cluster, please write up a short description of how that was done and send it to me, humphrey@cornell.edu, so that we can include it in our documentation.

First Step: Setting up your [[Cluster SSH access]].

Testing your access with [[pdsh commands]].

Next: Launching [[Mathematica Remote Kernels]].

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 Jobs can be sent to all nodes in the cluster, or a subset of the nodes.
-At this time, the cluster is working with ssh and Mathematica. We're in the process of getting it working with other applications including MPI, Matlab, Maple, and Magma. Check back on this page because support is rapidly evolving.
+At this time, the cluster is working with ssh MPI, Pari/gp using MPI, and Mathematica. We're in the process of getting it working with other applications including Matlab, Maple, and Magma. Many applications can be used for 'Pleasingly Parallel' workloads by running independent simultaneous programs using pdsh. Macaulay2 is available on all of the nodes for this purpose. Check back on this page because support is rapidly evolving.
-Also, if you can get your own application running on the cluster, please write up a short description of how that was done and send it to me, humphrey@cornell.edu, so that we can include it in our documentation.
+Also, if you can get your own application running on the cluster, please write up a short description and put it on this wiki! You can edit these pages, and create a page with your instructions, linked from this page.
 First Step: Setting up your [[Cluster SSH access]], including testing your access with pdsh commands.

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-[[File:Cluster.jpg|thumb|Picture of 64 node cluster on a metal shelf.]]
+[[File:Cluster-newstack.jpg|thumb|Picture of 64 node cluster on a metal shelf.]]
 == Math Cluster ==
 The Math Department has an experimental computational cluster. The main purpose is for configuring and testing distributed computing applications so that they can be run on larger clusters. However, since our recent upgrades, the computational cluster is very fast for certain workloads.

← Older revision		Revision as of 04:11, 28 September 2022
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		+	[[File:Cluster.jpg\|thumb\|Picture of 64 node cluster on a metal shelf.]]
−
−	[[File:Cluster-light2.jpg]]
	== Math Cluster ==		== Math Cluster ==
	The Math Department has an experimental computational cluster. It works fine for computation, but the main purpose is for configuring and testing distributed computing applications so that they can be run on larger clusters.		The Math Department has an experimental computational cluster. It works fine for computation, but the main purpose is for configuring and testing distributed computing applications so that they can be run on larger clusters.

← Older revision		Revision as of 04:05, 28 September 2022
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		+	[[File:Cluster-light2.jpg]]
	== Math Cluster ==		== Math Cluster ==
	The Math Department has an experimental computational cluster. It works fine for computation, but the main purpose is for configuring and testing distributed computing applications so that they can be run on larger clusters.		The Math Department has an experimental computational cluster. It works fine for computation, but the main purpose is for configuring and testing distributed computing applications so that they can be run on larger clusters.

← Older revision		Revision as of 16:37, 24 September 2022
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	Next: Launching [[Mathematica Remote Kernels]].		Next: Launching [[Mathematica Remote Kernels]].
		+
		+	MPI: Trying out the MPI 'Hello World' program, which is a step to running many types of parallel jobs. [[MPI Hello World]]

	Here is some info on running remote workers in Magma: [[Magma Cluster]] This is a work in progress since we don't have a nice, working example yet.		Here is some info on running remote workers in Magma: [[Magma Cluster]] This is a work in progress since we don't have a nice, working example yet.

← Older revision		Revision as of 20:28, 25 July 2022
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	Next: Launching [[Mathematica Remote Kernels]].		Next: Launching [[Mathematica Remote Kernels]].
		+
		+	Here is some info on running remote workers in Magma: [[Magma Cluster]] This is a work in progress since we don't have a nice, working example yet.

@@ Line 11: / Line 11: @@
 Also, if you can get your own application running on the cluster, please write up a short description of how that was done and send it to me, humphrey@cornell.edu, so that we can include it in our documentation.
-First Step: Setting up your [[Cluster SSH access]].
+First Step: Setting up your [[Cluster SSH access]], including testing your access with pdsh commands.
 Next: Launching [[Mathematica Remote Kernels]].