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Add new tutorials #607

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Jul 18, 2023
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Add new tutorials #607

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84fd65e
add new tutorials
sebastian-luna-valero Jul 17, 2023
f2ce04d
spelling
sebastian-luna-valero Jul 17, 2023
8990ff6
fix video link
sebastian-luna-valero Jul 17, 2023
9c288f3
Update exclusions, add FaaS
gwarf Jul 17, 2023
0c999fe
Disable copy paste detection
gwarf Jul 17, 2023
35cf553
Use a real link and a standard quote
gwarf Jul 17, 2023
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7 changes: 7 additions & 0 deletions .github/actions/spelling/allow.txt
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Expand Up @@ -198,6 +198,7 @@ eugridpma
eumed
eventlet
explorecube
FaaS
fakedomaindonotexist
faqs
fedcloud
Expand All @@ -219,6 +220,7 @@ gcloud
gcube
geant
genkey
geospatial
geoss
Gergely
getcontmsg
Expand Down Expand Up @@ -260,6 +262,7 @@ gsiscp
gsissh
gsoa
gstat
GUISDAP
hashicorp
haveged
hdds
Expand Down Expand Up @@ -372,6 +375,7 @@ Minio
mitaka
morecolor
mpi
MQS
multiattach
multidisk
mycluster
Expand All @@ -393,6 +397,7 @@ ndgf
ndownloader
nearline
neovim
NERGY
netfilters
neugrid
ngi
Expand Down Expand Up @@ -422,6 +427,7 @@ nsdbname
nsupdate
nsupdater
nvidia
OAIS
occi
ODV
ogf
Expand Down Expand Up @@ -532,6 +538,7 @@ slm
slurm
slurmserver
smes
Snakemake
softver
somekey
sourcing
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47 changes: 47 additions & 0 deletions content/en/users/tutorials/advanced/_index.md
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Expand Up @@ -306,4 +306,51 @@ ARC5-based deployment. Special attention will be given to the accounting system
and the new one-shop-stop sysadmin toolbox built around arcctl.
</td>
</tr>
<tr>
<td>
<b>Target Audience</b>: Scientific communities, developers, integrators and end users.
</td>
<td>
<i>"High performance software - Easy gains with simple CUDA" (April 2023)</i>
<br/><br/>
<iframe
width="560"
height="315"
src="https://www.youtube.com/embed/EyCCunB6u0c"
title="YouTube video player"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br/><br/>
<b>About</b>: This tutorial provides an introduction to CUDA in high
performance software, covering roughly these topics:
<ul>
<li>
Best practices for high performance software engineering,
such as avoiding premature optimization, ensuring cache alignment, etc.
</li>
<li>
A broad introduction to GPUs, including their hardware
and which categories of problems they are/aren't best suited for.
</li>
<li>Installing and working with GPU frameworks</li>
<li>An overview of profiler tools and how to use them</li>
<li>
A live coding session to implement and diagnose a basic CUDA program,
with the level of detail dependent on available time
</li>
<li>Q&A and stories from the trenches</li>
</ul>
Please note that the training will not cover multi-GPU setups or
provide a detailed dive into GPU hardware and CUDA specifics.
Participants should have basic knowledge of Python and matrix
computation libraries like NumPy.
<br/><br/>
<b>Slides and code</b>
<ul>
<li><a href="https://github.com/c-scale-community/cscale-gpet-workshop">https://github.com/c-scale-community/cscale-gpet-workshop</a></li>
</ul>
</td>
</tr>
</table>
89 changes: 89 additions & 0 deletions content/en/users/tutorials/intermediate/_index.md
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Expand Up @@ -525,4 +525,93 @@
</ul>
</td>
</tr>
<tr>
<td>
<b>Target Audience</b>: Scientific communities, for programmers and IT-service providers who support research and education.
</td>
<td>
<i>"Introduction to Slurm" (March 2023)</i>
<br/><br/>
<iframe
width="560"
height="315"
src="https://www.youtube.com/embed/2d0B9o43Pgg"
title="YouTube video player"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br/><br/>
<b>About</b>: Slurm is an open-source, fault-tolerant, and highly scalable
cluster management and job scheduling system for large and small Linux clusters.
In this tutorial, we briefly discuss the benefits of using batch schedulers,
the motivations to use Slurm and provide a list of commands to get started with Slurm.
<br/><br/>
<b>Suggested material</b>
<ul>
<li><a href="https://docs.google.com/presentation/d/1Qo_Zpqe9MT6X6s7o2Mz_8PplET28_WAf/">Slides</a></li>
</ul>
</td>
</tr>
<tr>
<td>
<b>Target Audience</b>: Scientific communities, for programmers and IT-service providers who support research and education.
</td>
<td>
<i>"Introduction to Snakemake" (December 2022)</i>
<br/><br/>
<iframe
width="560"
height="315"
src="https://www.youtube.com/embed/ktZf7sze1ug"
title="YouTube video player"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br/><br/>
<b>About</b>: The Snakemake workflow management system is a tool
for creating reproducible and scalable data analyses. Workflows
are described via a human-readable, Python-based language. They
can be seamlessly scaled to server, cluster, grid and cloud environments
without the need to modify the workflow definition. Finally, Snakemake
workflows can entail a description of the required software, which will
be automatically deployed to any execution environment.
<br/><br/>
<b>Slides and code</b>
<ul>
<li><a href="https://github.com/c-scale-community/c-scale-tutorial-snakemake/">https://github.com/c-scale-community/c-scale-tutorial-snakemake</a></li>
</ul>
</td>
</tr>
<tr>
<td>
<b>Target Audience</b>: Scientific communities, for programmers and IT-service providers who support research and education.
</td>
<td>
<i>"Leveraging the Onedata Platform for Long-Term Data Archiving" (June 2023)</i>
<br/><br/>
<iframe
width="560"
height="315"
src="https://www.youtube.com/embed/zXYOQEpQrHU"
title="YouTube video player"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br/><br/>
<b>About</b>: In this presentation, we will discuss the latest advancements
in the Onedata platform, focusing on its new features for long-term data
archiving and processing. We will demonstrate how the platform has been
optimized to meet the Open Archival Information System (OAIS) standards,
ensuring the reliable preservation and accessibility of archived information
over time. Furthermore, we will explore the integration of Function as a
Service (FaaS) capabilities in the platform, allowing for seamless and

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scalable data processing on demand. By combining the robust archiving
capabilities of the OAIS standard with the flexibility of FaaS, the Onedata

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platform emerges as a powerful solution for organizations seeking efficient
and reliable management of their long-term data storage and processing needs.
</td>
</tr>
</table>
145 changes: 145 additions & 0 deletions content/en/users/tutorials/scientific/_index.md
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Expand Up @@ -197,4 +197,149 @@ to serve COVID-related projects.
</ul>
</td>
</tr>
<tr>
<td>
<b>Target Audience</b>: Scientific communities working in the domain of Earth Observation.
</td>
<td>
<i>"C-SCALE Notebooks for Earth Observation" (June 2023)</i>
<br/><br/>
<iframe
width="560"
height="315"
src="https://www.youtube.com/embed/r34qGShiglY"
title="YouTube video player"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br/><br/>
<b>About</b>: The C-SCALE project has been federating compute and data resource providers
around centralized EGI services, aiming at providing users with seamless access to
processing capacities as well as source data for their analyses. Alongside the traditional
IaaS and PaaS services, Jupyter Notebooks have been identified as an environment suitable
not only for interactive analysis within C-SCALE, but also for documenting the different
steps one needs to take in discovering and accessing geospatial data across Europe.
The demonstration of C-SCALE's example notebooks and procedures will focus on those
essential features: simple steps to get started using the federated resources for
interactive resources of Earth Observation data.
<br/><br/>
<b>Slides and code</b>
<ul>
<li><a href="https://github.com/c-scale-community/c-scale-notebooks">https://github.com/c-scale-community/c-scale-notebooks</a></li>
</ul>
</td>
</tr>
<tr>
<td>
<b>Target Audience</b>: Scientific communities working in the domain of Earth Observation.
</td>
<td>
<i>"C-SCALE Earth Observation - Metadata Query Service" (March 2023)</i>
<br/><br/>
<iframe
width="560"
height="315"
src="https://www.youtube.com/embed/cebnrOgoX_I"
title="YouTube video player"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br/><br/>
<b>About</b>: The C-SCALE Earth Observation Metadata Query Service (EO-MQS)
makes Copernicus data distributed across providers within the C-SCALE Data
federation discoverable and searchable.
<br/><br/>
<b>Slides and code</b>
<ul>
<li><a href="https://github.com/c-scale-community/c-scale-tutorial-eo-mqs">https://github.com/c-scale-community/c-scale-tutorial-eo-mqs</a></li>
</ul>
</td>
</tr>
<tr>
<td>
<b>Target Audience</b>: Scientific communities working in the domain of Earth Observation.
</td>
<td>
<i>"Introduction to openEO Platform" (December 2022)</i>
<br/><br/>
<iframe
width="560"
height="315"
src="https://www.youtube.com/embed/pMiaBMh8VCQ"
title="YouTube video player"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br/><br/>
<b>About</b>: openEO platform provides intuitive programming libraries
to process a wide variety of earth observation datasets. This large-scale
data access and processing is performed on multiple infrastructures, which
all support the openEO API. This allows use cases from explorative research
to large-scale production of EO-derived maps and information.
<br/><br/>
<b>Slides and code</b>
<ul>
<li><a href="https://github.com/c-scale-community/c-scale-tutorial-openeo">https://github.com/c-scale-community/c-scale-tutorial-openeo</a></li>
</ul>
</td>
</tr>
<tr>
<td>
<b>Target Audience</b>: Scientific communities and end users.
</td>
<td>
<i>"I-NERGY, European AI-on demand platform" (July 2023)</i>
<br/><br/>
<iframe
width="560"
height="315"
src="https://www.youtube.com/embed/RUVzMiDCyb4"
title="YouTube video player"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br/><br/>
<b>About</b>: I-NERGY aims to support and develop novel AI-based energy
services as part of the enrichment of European AI-on demand platform.
This webinar will present the objectives and scope of the project,
its requirements in terms of resources and the successful utilisation
of EGI infrastructure. The webinar will conclude with a demo of I-NERGY services.
</td>
</tr>
<tr>
<td>
<b>Target Audience</b>: Scientific communities and end users.
</td>
<td>
<i>"Access to the EISCAT tools with help of EGI checkin" (June 2023)</i>
<br/><br/>
<iframe
width="560"
height="315"
src="https://www.youtube.com/embed/uucCLFRRW9w"
title="YouTube video player"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br/><br/>
<b>About</b>: The present era of rapid technological advances creates a
challenge for data providers and scientists to create and maintain FAIR
data and services not just for future operations but also for historical
data gathered and analysed with technologies that are slowly phasing out
of their usage. GUISDAP is an open-source software package, written in
MATLAB, C and Fortran and provided and maintained by EISCAT, for analysis
and visualisation of its incoherent scatter radar data as well as for some
other radars in the world. One way how to preserve GUISDAP operability
and accessibility by the user community is to make it accessible through
a Jupyter notebook docker deployment through EISCAT resources and in the
frame of an EOSC project. This will help to ensure the FAIRness of EISCAT
data by providing tools for reanalysis and visualisation that will be
accessible by any potential EISCAT user with the help of EGI check-in technology.
</td>
</tr>
</table>
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