Data on Triton

This section gives an best practices data usage, access and transfer to and from Triton.


For data transfer, we assume that you have set up your system according to the instructions in the quick guide

Locations and quotas








$HOME or /home/USERNAME/

hard quota 10GB


all nodes

Small user specific files, no calculation data.


$WRKDIR or /scratch/work/USERNAME/

200GB and 1 million files


all nodes

Personal working space for every user. Calculation data etc. Quota can be increased on request.



on request


all nodes

Department/group specific project directories.

Local temp


limited by disk size



Primary (and usually fastest) place for single-node calculation data. Removed once user’s jobs are finished on the node.

Local persistent




dedicated group servers only

Local disk persistent storage. On servers purchased for a specific group. Not backed up.

ramfs (login nodes only)


limited by memory



Ramfs on the login node only, in-memory filesystem

Access to data and data transfer


On Windows systems, this guide assumes that you use GIT-bash, and have rsync installed according to this guide

Download data to Triton

To download a dataset directly to Triton, if it is available somewhere online at a URL, you can use wget:


If the data requires a login you can use:

wget --user username --ask-password

Downloading directly to Triton allows you to avoid the unnecessary network traffic and time required to first download it to your machine and then transferring it over to Triton.

If you need to download a larger (>10GB) dataset to Triton from the internet please verify that the download actually succeeded properly. This can be done by comparing the md5 checksum (or others using e.g. sha256sum and so on), commonly provided by hosts along with the downloadable data. The resulting checksum has to be identical to the one listed online. If it is not, your data is most likely corrupted and should not be used. After downloading simply run:

md5sum downloadedFileName

For very large datasets (>100GB) you should check, whether they are already on Triton. The folder for these kinds of datasets is located at: /scratch/shareddata/dldata/, and if not, please contact the admins to have it added there. This avoids the same dataset being downloaded multiple times.

Copy data to and from Triton

The folders available on Triton are listed above. To copy small amounts of data to and from Triton from outside the Aalto network, you can either use scp or on linux/mac mount the file-system using sftp (e.g. sftp://triton_via_kosh).

From inside the Aalto network (or VPN), you can also mount the Triton file system via smb (More details can be found here):

  • scratch: smb://

  • work: smb://$username/.

For larger files, or folders with multiple files and if the data is already on your machine, we suggest using rsync (For more details on rsync have a look here):

# Copy PATHTOLOCALFOLDER to your Triton home folder
rsync -avzc -e "ssh" PATHTOLOCALFOLDER triton_via_kosh:/home/USERNAME/
# Copy PATHTOTRITONFOLDER from your Triton home folder to LOCALFOLDER
rsync -avzc -e "ssh" triton_via_kosh:/home/USERNAME/PATHTOTRITONFOLDER LOCALFOLDER triton_via_kosh:/home/USERNAME/

Best practices with data

I/O can be a limiting factor when using the cluster. The probably most important factor limiting I/O speed on Triton is file-sizes. The smaller the files the more inefficient their transfer. When you run a job on Triton and need to access many small files, we recommend to first pack them into a large tarball:

# To tar, and compress a folder use the following command
tar -zcvf mytarball.tar.gz folder
# To only bundle the data (e.g. if you want to avoid overhead by decompressing)
# a folder use the following command
tar -cvf mytarball.tar folder

copy them over to the node where your code is executed and extract them there within the slurm script or your code.

# copy it over
cp mytarball.tar /tmp
# and extract it locally
tar -xf /tmp/mytarball.tar

If each input file is only used once, it’s more efficient to load the tarball directly from the network drive. If it fits into memory, load it into memory, if not, try to use a sequentially reading input method and have the required files in the tar-ball in the required order. For more information on storage and data usage on Triton have a look at these documents: