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rewrite abstract to include CernVM-FS
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What if there was a way to avoid having to install a broad range of scientific software from scratch on every HPC | ||
cluster or cloud instance you use or maintain, without compromising on performance? | ||
What if there was a way to avoid having to install a broad range of scientific software from scratch on every | ||
supercomputer, cloud instance, or laptop you use or maintain, without compromising on performance? | ||
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Installing scientific software for supercomputers is known to be a tedious and time-consuming task. The application | ||
software stack continues to deepen as the | ||
HPC user community becomes more diverse, computational science expands rapidly, and the diversity of system architectures | ||
High-Performance Computing (HPC) user community becomes more diverse, computational science expands rapidly, and the diversity of system architectures | ||
increases. Simultaneously, we see a surge in interest in public cloud | ||
infrastructures for scientific computing. Delivering optimised software installations and providing access to these | ||
installations in a reliable, user-friendly, and reproducible way is a highly non-trivial task that affects application | ||
developers, HPC user support teams, and the users themselves. | ||
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This tutorial aims to address these challenges by providing the attendees with the tools to \emph{stream} the optimised | ||
scientific software they need. The tutorial introduces European Environment for Scientific Software Installations | ||
(\emph{EESSI}), a collaboration between various European HPC sites \& industry partners, with the common goal of | ||
creating a shared repository of scientific software installations (\emph{not} recipes) that can be used on a variety of | ||
systems, regardless | ||
of which flavor/version of Linux distribution or processor architecture is used, or whether it's a full size HPC | ||
Although scientific research on supercomputers is fundamentally software-driven, | ||
setting up and managing a software stack remains challenging and time-consuming. | ||
In addition, parallel filesystems like GPFS and Lustre are known to be ill-suited for hosting software installations | ||
that typically consist of a large number of small files. This can lead to surprisingly slow startup performance of | ||
software, and may even negatively impact the overall performance of the system. | ||
While workarounds for these issues such as using container images are prevalent, they come with caveats, | ||
such as the significant size of these images, the required compatibility with the system MPI for distributing computing, | ||
and complications with accessing specialized hardware resources like GPUs. | ||
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This tutorial aims to address these challenges by introducing the attendees to a way to \emph{stream} | ||
software installations via \emph{CernVM-FS}, a distributed read-only filesystem specifically designed | ||
to efficiently distribute software across large-scale computing infrastructures. | ||
The tutorial introduces the \emph{European Environment for Scientific Software Installations (EESSI)}, | ||
a collaboration between various European HPC sites \& industry partners, with the common goal of | ||
creating a shared repository of optimised scientific software installations (\emph{not} recipes) that can be used on a variety of | ||
systems, regardless of which flavor/version of Linux distribution or processor architecture is used, or whether it's a full size HPC | ||
cluster, a cloud environment or a personal workstation. | ||
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We cover the usage of EESSI, different ways to accessing EESSI, how to add software to EESSI, and highlight some more | ||
advanced features. We will also show attendees how to engage with the community and contribute to the project. | ||
We cover the installation and configuration of CernVM-FS to access EESSI, the usage of EESSI, how to add software | ||
installations to EESSI, how to install software on top of EESSI, and advanced topics like GPU support and performance | ||
tuning. |