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Overview The DISCOVERY general purpose Cluster is an exciting opportunity for researchers to participate in creating a world class super computer devoted to furthering research at Dartmouth

, large memory programs quickly and efficiently; and store data securely and accessibly. Click here for more information about the cluster. Click here to gain information on how to access the Discovery cluster

Discovery is a Linux cluster that in aggregate contains 128 nodes, 6296 CPU cores, 54.7TB of memory, and more than 2.8 PB of disk space. Node Hardware Breakdown Cell Vendor

Access to Discovery cluster from Macintosh ... discovery-NETID.terminal ... Windows. To display graphical output from remote Linux software, you'll need Xquartz or FastX (see below), but this isn't so important with discovery since it is a batch-scheduled environment

30th. Over the coming weeks, we'll be migrating batches of compute nodes. During this time, you may notice a decrease in available resources within the discovery7 cluster, with more resources becoming

discovery ... interactive RStudio session on the Discovery HPC Cluster.   STEP 1:  Connect to discovery using your username and password  Either connect directly to desired node if your department has

Step by step instructions for migrating data from a legacy Discovery home directory to a DartFS home directory. ... Background New home directories for Research Computing servers are in DartFS.  When you have a DartFS home directory you can login to all of our systems (Discovery, Polaris, Andes, etc.) using

about requesting an account to get started with Andes  Discovery uses a 'scheduler' program to submit jobs to a queue, rather than interactively (for example, .m Matlab programs can be

Details The following software is available to researchers: Bioinformatics Software Availability OS Comments mrbayes Discovery Linux

The following steps demo: Create a job submission script to run a Jupyter notebook on the Discovery cluster Submit the job to the scheduler Create a SSH tunnel to Discovery and browse to

/ .  To use software on our high-performance computers (Andes, Polaris or Discovery), please visit https://rc.dartmouth.edu/ and click "Request an account" to get started, and for instructions on

In this lab we will create a basic R script to print "Hello World!". Then we will use the scheduler to submit the job via sbatch. The first step of this process is to either move your R script

In this lab we will use openMPI to compile a very basic "Hello World!" script, which we will then submit to run across multiple compute nodes. Once you have logged into the discovery cluster. The

In this lab we will create a simple python script, called invert_matrix.py which we will submit to the cluster. In addition we will explore what it is like for a job to run out of walltime. For the

/ .  To use software on our high-performance computers (Andes, Polaris or Discovery), please visit https://rc.dartmouth.edu/ and click "Request an account" to get started, and for instructions on