Phriction Projects Wikis Bioimaging And Optics Platform Computers & Servers at the BIOP sv-renku.epfl.ch History Version 10 vs 11
Version 10 vs 11
Version 10 vs 11
Edits
Edits
- Edit by romainGuiet, Version 11
- Sep 7 2021 12:20
- Edit by romainGuiet, Version 10
- Jul 26 2021 14:02
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Content Changes
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= RENKU's motto=
(NOTE) **"Renku makes it simple to reuse code and data in other projects." **
Renku is freely accessible at [[ https://renkulab.io/| https://renkulab.io/]] with free project creation and free computing power (up to 2 CPU and 8 G RAM).
The SV-IT installed and take care of a "private" RENKU, accessible at [[ sv-renku.epfl.ch | sv-renku.epfl.ch]], which is currently equipped with 8 K40 GPUs ([[ https://en.wikipedia.org/wiki/Nvidia_Tesla | Nvidia K40 ]])
**Only** the users from SV have a direct access ( //via// gaspar login).
Users from a different faculty can request a "test" access, //via // email to SV-IT to Nicolas Barriere.
= RENKU BIOP usage =
(NOTE) We see in RENKU a powerful tool to ease the access to cutting edge DeepLearning tools
(WARNING) BUT it's also much more, please visit [[ https://renkulab.io/ | renkulab ]] )
=== Why using RENKU ? ===
If you ever tried to re-use a python project from someone else, you may have encountered some issue with the installation process.
Indeed, you can do some pip install, some conda install, some other packages might need to be build from source.
In case you work with GPUs, you also need to take care of the installation of drivers and extra libraries to make all of this work.
If you want to install this project on a new computer, with some new hardware, suddenly all of this needs to be done again (sometimes from scratch!)
(NOTE) RENKU can help us with the tedious installation part, as the job needs to be done ONCE (with the help of the **//BIOP //**and **//SV-IT//** if needed) and then shared with all other RENKU users!
= RENKU Tutorial =
you can test the
- Brainreg demo on [[ https://renkulab.io/projects/guiet.romain/brainreg | renkulab.io/brainreg ]] using this short tutorial:
{F20200198}
- StarDist demo on [[ https://sv-renku.epfl.ch/projects/guiet/run-vnc-omero-fiji-napari-stardist/environments/new | sv-renku/stardist ]]
= RENKU new project=
You can easily start a new project, using the button {key New_project}
{F20200256}
You'll have to define a name
{F20200271}
and if you want to use a **`RENKU`** template
{F20200280}
or a **`CUSTOM`** template
{F20200309}
in which case you need to specify the github page, branch (usually main) and then fetch template :
{F20200380}
= Some CUSTOM Templates =
Some templates can be found on the [[ https://github.com/BIOP/renku-templates | BIOP github page ]] which are adapted from [[ https://github.com/gavin-k-lee/contributed-project-templates | SDSC pages ]].
(NOTE) Using this template you'll get access to a JupyterLab, an Ubuntu desktop (via VNC), Fiji and Napari are pre-installed and you can download data from [[ https://omero.epfl.ch/ | OMERO]] and optionally use `CUDA10.1`
= Some Existing projects =
| Main tool name | RENKU project | RENKU project spec. |
| yapic | RENKU project | python3.7 , CUDA 10.1 , CUDDN 7.6.5, TensorFlow 2.1 |
| brainreg | [[ https://sv-renku.epfl.ch/projects/guiet/brainreg | sv-renku.epfl.ch/brainreg ]] | No GPU , OMERO |
| cellpose | RENKU project | python3.8 , python3.7 , CUDA 10.0, CUDDN 7.4.1.5 , pytorch-GPU 1.3.1 |
| stardist | [[ https://sv-renku.epfl.ch/projects/guiet/run-vnc-omero-fiji-napari-stardist | sv-renku.epfl.ch/run-vnc-omero-fiji-napari-stardist ]] | TensorFlow 1.15 , CUDA 10.1 |
| denoiseg | [[ https://sv-renku.epfl.ch/projects/guiet/denoiseg | sv-renku.epfl.ch/denoiseg ]] | python3.7 , CUDA 10.1 , CUDDN 7.6.5, TensorFlow 1.15, Keras 2.2.5 |
| OPT | [[ https://sv-renku.epfl.ch/projects/guiet/opt | sv-renku.epfl.ch/opt ]] | Astra-toolbox |
| ... | ... | ... |
| cuda11-0-cudnn8 | [[ https://sv-renku.epfl.ch/projects/nbarrier/cuda11-0-cudnn8/files/blob/Dockerfile | cuda11-0-cudnn8]] | CUDA 11.0 , CUDDN 8 |
| ... | ... | ... |
= RENKU's motto=
(NOTE) **"Renku makes it simple to reuse code and data in other projects." **
Renku is freely accessible at [[ https://renkulab.io/| https://renkulab.io/]] with free project creation and free computing power (up to 2 CPU and 8 G RAM).
The SV-IT installed and take care of a "private" RENKU, accessible at [[ sv-renku.epfl.ch | sv-renku.epfl.ch]], which is currently equipped with 8 K40 GPUs ([[ https://en.wikipedia.org/wiki/Nvidia_Tesla | Nvidia K40 ]])
**Only** the users from SV have a direct access ( //via// gaspar login).
Users from a different faculty can request a "test" access, //via // email to SV-IT to Nicolas Barriere.
= RENKU BIOP usage =
(NOTE) We see in RENKU a powerful tool to ease the access to cutting edge DeepLearning tools
(WARNING) BUT it's also much more, please visit [[ https://renkulab.io/ | renkulab ]] )
=== Why using RENKU ? ===
If you ever tried to re-use a python project from someone else, you may have encountered some issue with the installation process.
Indeed, you can do some pip install, some conda install, some other packages might need to be build from source.
In case you work with GPUs, you also need to take care of the installation of drivers and extra libraries to make all of this work.
If you want to install this project on a new computer, with some new hardware, suddenly all of this needs to be done again (sometimes from scratch!)
(NOTE) RENKU can help us with the tedious installation part, as the job needs to be done ONCE (with the help of the **//BIOP //**and **//SV-IT//** if needed) and then shared with all other RENKU users!
= RENKU Tutorial =
you can test the
- Brainreg demo on [[ https://renkulab.io/projects/guiet.romain/brainreg | renkulab.io/brainreg ]] using this short tutorial:
{F20200198}
- StarDist demo on [[ https://sv-renku.epfl.ch/projects/guiet/run-vnc-omero-fiji-napari-stardist/environments/new | sv-renku/stardist ]]
= RENKU new project=
You can easily start a new project, using the button {key New_project}
{F20200256}
You'll have to define a name
{F20200271}
and if you want to use a **`RENKU`** template
{F20200280}
or a **`CUSTOM`** template
{F20200309}
in which case you need to specify the github page, branch (usually main) and then fetch template :
{F20200380}
= Some CUSTOM Templates =
Some templates can be found on the [[ https://github.com/BIOP/renku-templates | BIOP github page ]] which are adapted from [[ https://github.com/gavin-k-lee/contributed-project-templates | SDSC pages ]].
(NOTE) Using this template you'll get access to a JupyterLab, an Ubuntu desktop (via VNC), Fiji and Napari are pre-installed and you can download data from [[ https://omero.epfl.ch/ | OMERO]] and optionally use `CUDA10.1`
= Some Existing projects =
| Main tool name | RENKU project | RENKU project spec. |
| yapic | [[ https://sv-renku-git.epfl.ch/guiet/template-tensorflow-tensorboard-gpu-cuda-10.1 | sv-renku.epfl.ch/yapic ]] | python3.7 , CUDA 10.1 , CUDDN 7.6.5, TensorFlow 2.1 |
| brainreg | [[ https://sv-renku.epfl.ch/projects/guiet/brainreg | sv-renku.epfl.ch/brainreg ]] | No GPU , OMERO |
| cellpose | [[ https://sv-renku-git.epfl.ch/guiet/vnc-omero-fiji-cellpose-test | sv-renku.epfl.ch/cellpose ]] | python3.8 , python3.7 , CUDA 10.0, CUDDN 7.4.1.5 , pytorch-GPU 1.3.1 |
| stardist | [[ https://sv-renku.epfl.ch/projects/guiet/run-vnc-omero-fiji-napari-stardist | sv-renku.epfl.ch/run-vnc-omero-fiji-napari-stardist ]] | TensorFlow 1.15 , CUDA 10.1 |
| denoiseg | [[ https://sv-renku.epfl.ch/projects/guiet/denoiseg | sv-renku.epfl.ch/denoiseg ]] | python3.7 , CUDA 10.1 , CUDDN 7.6.5, TensorFlow 1.15, Keras 2.2.5 |
| OPT | [[ https://sv-renku.epfl.ch/projects/guiet/opt | sv-renku.epfl.ch/opt ]] | Astra-toolbox |
| ... | ... | ... |
| cuda11-0-cudnn8 | [[ https://sv-renku.epfl.ch/projects/nbarrier/cuda11-0-cudnn8/files/blob/Dockerfile | cuda11-0-cudnn8]] | CUDA 11.0 , CUDDN 8 |
| ... | ... | ... |
= RENKU's motto=
(NOTE) **"Renku makes it simple to reuse code and data in other projects." **
Renku is freely accessible at [[ https://renkulab.io/| https://renkulab.io/]] with free project creation and free computing power (up to 2 CPU and 8 G RAM).
The SV-IT installed and take care of a "private" RENKU, accessible at [[ sv-renku.epfl.ch | sv-renku.epfl.ch]], which is currently equipped with 8 K40 GPUs ([[ https://en.wikipedia.org/wiki/Nvidia_Tesla | Nvidia K40 ]])
**Only** the users from SV have a direct access ( //via// gaspar login).
Users from a different faculty can request a "test" access, //via // email to SV-IT to Nicolas Barriere.
= RENKU BIOP usage =
(NOTE) We see in RENKU a powerful tool to ease the access to cutting edge DeepLearning tools
(WARNING) BUT it's also much more, please visit [[ https://renkulab.io/ | renkulab ]] )
=== Why using RENKU ? ===
If you ever tried to re-use a python project from someone else, you may have encountered some issue with the installation process.
Indeed, you can do some pip install, some conda install, some other packages might need to be build from source.
In case you work with GPUs, you also need to take care of the installation of drivers and extra libraries to make all of this work.
If you want to install this project on a new computer, with some new hardware, suddenly all of this needs to be done again (sometimes from scratch!)
(NOTE) RENKU can help us with the tedious installation part, as the job needs to be done ONCE (with the help of the **//BIOP //**and **//SV-IT//** if needed) and then shared with all other RENKU users!
= RENKU Tutorial =
you can test the
- Brainreg demo on [[ https://renkulab.io/projects/guiet.romain/brainreg | renkulab.io/brainreg ]] using this short tutorial:
{F20200198}
- StarDist demo on [[ https://sv-renku.epfl.ch/projects/guiet/run-vnc-omero-fiji-napari-stardist/environments/new | sv-renku/stardist ]]
= RENKU new project=
You can easily start a new project, using the button {key New_project}
{F20200256}
You'll have to define a name
{F20200271}
and if you want to use a **`RENKU`** template
{F20200280}
or a **`CUSTOM`** template
{F20200309}
in which case you need to specify the github page, branch (usually main) and then fetch template :
{F20200380}
= Some CUSTOM Templates =
Some templates can be found on the [[ https://github.com/BIOP/renku-templates | BIOP github page ]] which are adapted from [[ https://github.com/gavin-k-lee/contributed-project-templates | SDSC pages ]].
(NOTE) Using this template you'll get access to a JupyterLab, an Ubuntu desktop (via VNC), Fiji and Napari are pre-installed and you can download data from [[ https://omero.epfl.ch/ | OMERO]] and optionally use `CUDA10.1`
= Some Existing projects =
| Main tool name | RENKU project | RENKU project spec. |
| yapic | RENKU project[[ https://sv-renku-git.epfl.ch/guiet/template-tensorflow-tensorboard-gpu-cuda-10.1 | sv-renku.epfl.ch/yapic ]] | python3.7 , CUDA 10.1 , CUDDN 7.6.5, TensorFlow 2.1 |
| brainreg | [[ https://sv-renku.epfl.ch/projects/guiet/brainreg | sv-renku.epfl.ch/brainreg ]] | No GPU , OMERO |
| cellpose | RENKU project[[ https://sv-renku-git.epfl.ch/guiet/vnc-omero-fiji-cellpose-test | sv-renku.epfl.ch/cellpose ]] | python3.8 , python3.7 , CUDA 10.0, CUDDN 7.4.1.5 , pytorch-GPU 1.3.1 |
| stardist | [[ https://sv-renku.epfl.ch/projects/guiet/run-vnc-omero-fiji-napari-stardist | sv-renku.epfl.ch/run-vnc-omero-fiji-napari-stardist ]] | TensorFlow 1.15 , CUDA 10.1 |
| denoiseg | [[ https://sv-renku.epfl.ch/projects/guiet/denoiseg | sv-renku.epfl.ch/denoiseg ]] | python3.7 , CUDA 10.1 , CUDDN 7.6.5, TensorFlow 1.15, Keras 2.2.5 |
| OPT | [[ https://sv-renku.epfl.ch/projects/guiet/opt | sv-renku.epfl.ch/opt ]] | Astra-toolbox |
| ... | ... | ... |
| cuda11-0-cudnn8 | [[ https://sv-renku.epfl.ch/projects/nbarrier/cuda11-0-cudnn8/files/blob/Dockerfile | cuda11-0-cudnn8]] | CUDA 11.0 , CUDDN 8 |
| ... | ... | ... |
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