Access Abstraction to HPC Resources - Virtual Event

Akademie I (Empa)

Akademie I


Überlandstrasse 129 8600 Dübendorf
Carlo Pignedoli (Empa) , Daniele Passerone (Empa) , Edoardo Baldi (Empa) , Michele De Lorenzi (ETH Zurich / CSCS)


For HPC centers it is essential to simplify the access to the computational resources for their user  communities. Personal computing did already introduce in the eighties of last century the concept of desktop computing to simplify the utilization by the users. At the same time we moved from mainframes to client-server architectures up to micro-services. Unfortunately supercomputers are still (mostly) used by manually submitting jobs in queues.

Some scientific communities did already work on such challenges and created web portals able to support complex workflow hiding from the end users details related to the HPC infrastructure. More and more scientists will be involved in the next few years in building such platforms.

For us it is getting more and more important to support those portals and offer new ways to use the computational and storage resources we manage. It shall be possible to use the supercomputers interactively or through defined programmatic interfaces (API) to cover from simple use cases up to complex workflows. This also includes access to data management tools to stage in (and out) everything that’s needed to run the simulation or analysis.

Key Questions

  • Scientific portals: What kind of scientific portals do exist today? What will be the future developments? What are their requirements respect to the HPC providers?

  • Interactive computing platforms: How can I easily run a calculation/analysis that requires some degree of interaction on a bigger and more powerful machine? Can I use an HPC resource as if it was my laptop?

  • Efficient management of data: Are there any optimal tools to manage data efficiently? E.g., avoiding copying non-essential info when moving data, or saving data for archiving purposes  Can I synchronize files between my computer, my home institution and my HPC resource without having to use too many different tools? Without having to monitor failures manually?

  • Computational resources abstraction: As a HPC provider, how can we build a “middle layer” allowing our scientific computing users to see the resources we are providing in a uniform way? (keywords: workflow, API, RESTful interfaces).

  • Adam Henderson
  • Alain Studer
  • Alexander Kashev
  • Alexandre Wetzel
  • Alfio Lazzaro
  • Allen Neeser
  • Andrei Plamada
  • Anibal Moreno
  • Antonio Russo
  • Carlo Antonio Pignedoli
  • Carlos Fenoy
  • Christian Bolliger
  • Daniele Passerone
  • Edoardo Baldi
  • Eirini Koutsaniti
  • Elmar Dette
  • Enrico Favero
  • Filippo Stenico
  • Fotis Georgatos
  • Gianfranco Sciacca
  • Giovanni Pizzi
  • Guillermo Losilla
  • Hans-Rudolf Hotz
  • Hardik Kothari
  • Heinrich Billich
  • Jean-Baptiste Aubort
  • Jean-Claude De Giorgi
  • Kristjan Eimre
  • Leonardo Sala
  • Maria Grazia Giuffreda
  • Martin Jacquot
  • Massimo Brero
  • Maxime Martinasso
  • Mei-Chih Chang
  • Michael Niedermann
  • Michele De Lorenzi
  • Nicolas Kowenski
  • Olivier Byrde
  • Pablo Fernandez
  • Pascal Häussler
  • Patrick Bleiziffer
  • Patrick Zosso
  • Radim Janalík
  • Raluca Hodoroaba
  • Rene Windiks
  • Ricardo Silva
  • Roberto Fabbretti
  • Rok Roškar
  • Sean Hughes
  • Sofiane Sarni
  • Stefano Gorini
  • Sébastien Moretti
  • Thomas Kramer
  • Thomas Wüst
  • Tim Robinson
  • Ulrich Tehrani
  • Victor Holanda