This guide pertains to the new configuration of the HPC
cluster which is now available. Use this guide for all current and future work.
You can see the user guide for our previous cluster configuration
here - HPC Basic Use Guide - but please begin migrating your workflows
to the configuration described in this page as soon as possible before the old configuration is
retired in November.
The CHTC high-performance computing (HPC) cluster provides dedicated support for large,
singular computations that use specialized software (i.e. MPI) to achieve internal
parallelization of work across multiple servers of dozens to hundreds of cores.
Is high-performance computing right for me? Only computational work that
fits that above description is permitted on the HPC. All other computational
work, including single and multi-core (but single node) processes, that each complete
in less than 72 hours on a single node will be
best supported by our larger high-throughput computing (HTC) system (which also
includes specialized hardware for extreme memory, GPUs, and other cases). For more
information about high-throughput computing, please see Our Approach.
To get access to the HPC, please complete our
Large-Scale Computing Request Form. After your account request is received,
our Research Computing Facilitators will follow up with you and schedule a meeting
to discuss the computational needs of your research and connect you with computing
resources (including non-CHTC services) that best fit your needs.
New HPC Configuration
Roll out of the new HPC configuration is currently scheduled for late Sept./early Oct.
More information about our HPC upgrade and user migration timeline was sent out to
users by email. All CHTC user email correspondences are available at User News.
The new HPC configuration will include the following changes:
upgrade of operating system from Scientific Linux release 6.6 to CentOS 7
upgrade of SLURM from version 2.5.1 to version 20.02.2
upgrades to filesystems and user data and software management
a new set of modules and software
new head node hostnames
The above changes will result in a new HPC computing environment
and will provide users with new SLURM features and improved support and reliability
for their HPC work.
HPC User Policies
Below is a list of policies that apply to all HPC users.
1. Do Not Run Programs On The Login Nodes
When you connect to the HPC, you are connected to a login node. The HPC login nodes have
limited computing resources that are occupied with running Slurm and managing job submission.
Users should only run basic commands (like tar, cp, mkdir) on the login nodes. The
execution of scripts, including cron, software, and software compilation on the login nodes
is prohibited (and could VERY likely crash the head node). However, users may run small scripts
and commands (to compress data, create directories, etc.) that run within a few minutes but
their use should be minimized when possible. If you are unsure if your scripts are suitable
for running on the login nodes, please contact us at chtc@cs.wisc.edu.
CHTC staff reserve the right to kill any long-running or problematic processes on the
head nodes and/or disable user accounts that violate this policy
Violation of these policies may result in suspension of your account.
2. The HPC Is Reserved For MPI-enabled, Multi-node Jobs
HPC users should not submit single-core or single-node jobs to the HPC. Users will
be asked to transition this kind of work to our high-throughput computing system.
3. HPC File System Is Not Backed-up
All files on the HPC should be treated as temporary and only files necessary for
actively running jobs should be kept on the file system. Once your jobs complete,
your files should be removed from the HPC. Campus researchers have several options
for data storage solutions, including ResearchDrive
which provides up to 5TB of storage for free. Our guide
Transferring Files Between CHTC and ResearchDrive provides
step-by-step instructions for transferring your data to and from the HPC and RsearchDrive.
CHTC Staff reserve the right to remove any significant amounts of data on the HPC Cluster
in our efforts to maintain filesystem performance for all users, though we will always
first ask users to remove excess data and minimize file counts before taking additional action.
4. Fair-share Policy
To promote fair access to HPC computing resources, all users are limited to 10 concurrently
running jobs at a time. Additionally, user are restricted to a total of 600 cores
across all running jobs. Core limits do not apply on research group partitions of
more than 600 cores.
5. Job Priority Policy
A. User priority decreases as the user accumulates hours of CPU time over the last 21 days, across
all queues. This “fair-share” policy means that users who have run many/larger jobs in the near-past
will have a lower priority, and users with little recent activity will see their waiting jobs start sooner. We do
NOT have a strict “first-in-first-out” queue policy.
B. Job priority increases with job wait time. After the history-based user priority calculation in (A),
the next most important factor for each job’s priority is the amount of time that each job has already
waited in the queue. For all the jobs of a single user, these jobs will most closely follow a “first-in-first-out” policy.
C. Job priority increases with job size, in cores. This least important factor slightly favors larger jobs, as a means of
somewhat countering the inherently longer wait time necessary for allocating more cores to a single job.
HPC Hardware and Configuration
The HPC Cluster consists of two login nodes and many compute (aka execute)
nodes. All users log in at a login node, and all user files
on the shared file sytem are accessible on all nodes.
Additionally, all nodes are tightly networked (56 Gbit/s Infiniband) so
they can work together as a single "supercomputer", depending on the
number of CPUs you specify. All execute and head nodes are running the Linux
operating system CentOS version 7.
Only execute nodes will be used for performing your computational work.
The execute nodes are organized into several "partitions", including
the univ, univ2, pre, and int partitions which are available to
all HPC users as well as research group specific partitions that consist
of researcher owned hardware and which all HPC users can access on a
backfill capacity via the pre partition (more details below).
Partitions
Partition
p-name
# nodes (N)
t-max
t-default
max nodes/job
cores/node (n)
RAM/node (GB)
University 2
univ2
148
7 days
1 day
16
20
128
Interactive
int
6
1 hr
1hr
1
20
128
Pre-emptable (backfill)
pre
316
24 hrs
4 hrs
16
20
128
Owners
unique
124
7 days
24 hrs
unique
20
128
Astronomy Dept (differs)
astro3
24
4 days
24 hrs
16
20
128
univ2 consists of our second generation compute nodes, each with 20
CPU cores of 2.5 GHz and 128 GB of RAM. Like univ, jobs submitted to this partition
will not be pre-empted and can run for up to 7 days.
int consists of two compute nodes is intended for short and immediate interactive
testing on a single node (up to 16 CPUs, 64 GB RAM). Jobs submitted to this partition
can run for up to 1 hour.
pre (i.e. pre-emptable) is an under-layed partition encompassing all HPC compute
nodes. This partiton is intended for more immediate turn-around of shorter and somewhat
smaller jobs, or for interactive sessions requiring more than the 30-minute limit of
the int partition. Jobs submitted to pre are pre-emptable and can run for up to 24
hours. pre partition jobs will run on any idle nodes, including researcher owned
compute nodes nodes, as back-fill meaning these jobs may be pre-empted by higher priority
jobs. However, pre-empted jobs will be re-queued when submitted with an sbatch script.
Operating System and Software
All nodes in the HPC Cluster are running CentOS 7 Linux.
The SLURM scheduler version is 20.02.2.
To see more details of other software on the cluster, see the HPC Software page.
Data Storage and Management
Data space in the HPC file system is not backed-up and should be
treated as temporary by users. Only files necessary for
actively-running jobs should be kept on the file system, and files
should be removed from the cluster when jobs complete. A copy of any
essential files should be kept in an alternate, non-CHTC storage
location.
Each user will receive two primary data storage locations:
/home/username with an initial disk quota of 100GB
and 10,000 items. With the exception of software, all of the files
needed for your work, such as input, output, configuration files, etc.
should be located in your /home directory.
/software/username with an initial disk quota of 10GB and
100,000 items. All software, library, etc. installtions should
be written to and located in your /software directory.
To check how many files and directories you have in
your /home or /software directory see the
instructions below.
Increased quotas to either of these locations are available upon email
request to chtc@cs.wisc.edu. In your request,
please include both size (in GB) and file/directory counts. If you don't
know how many files your installation creates, because it's more than
the current items quota, simply indicate that in your request.
CHTC Staff reserve the right to remove any significant amounts of data
on the HPC Cluster in our efforts to maintain filesystem performance
for all users, though we will always first ask users to remove excess
data and minimize file counts before taking additional action.
Local scratch space of 500 GB is available on each execute node in
/scratch/local/$USER and is automatically cleaned out upon completion
of scheduled job sessions (interactive or non-interactive). Local
scratch is available on the login nodes, hpclogin1 and hpclogin2, also at
/scratch/local/$USER and should be cleaned out by the user upon completion of
compiling activities. CHTC staff will otherwise clean this location of
the oldest files when it reaches 80% capacity.
Tools for managing home and software space
You can use the command get_quotas to see what disk
and items quotas are currently set for a given directory path.
This command will also let you see how much disk is in use and how many
items are present in a directory:
When ncdu has finished running, the output will give you a total file
count and allow you to navigate between subdirectories for even more
details. Type q when you're ready to exit the output viewer. More
info here: https://lintut.com/ncdu-check-disk-usage/
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