Project Details

Standard Grant

Extreme Computing For Advanced Methods of Solving PDEs

Today's global challenges in the energy, aerospace and biotechnology sectors require extreme engineering approaches that take into account the complex interplay of different physical processes that operate at multiple length and time scales. The effective collaboration of domain scientists who have access to a European infrastructure for supercomputing applications is essential to accelerate research in these areas, providing the simulation tools that will enable European industry to be highly innovative and internationally competitive.

The project has two broad aims. Firstly, it will foster a network of European scientists who are researching advanced methods for solving partial differential equations. The methods include, but are not limited to, the finite element method, the extended finite element method and meshfree methods. Secondly, using the DECI resources requested, the team will implement and deploy a "Virtual Laboratory" for materials characterisation that will be used to evaluate the response of exemplar high performance engineering materials to a range of insilico tests.
The materials will be scanned at a high resolution using a state of the art X-ray tomography scanning facility at the University of Manchester. The resulting 3D images will be converted into micro-structurally faithful computer models. Finally, stress, thermal, vibration and fracture mechanics tests will be carried out, not one after another, but at the same time using multiple supercomputers simultaneously.

This work is particularly exciting because extremes of temperature, pressure and vibration, which are experienced by materials in the energy, space and aerospace sectors, are difficult and costly to recreate in the laboratory. In contrast, with the necessary computing infrastructure, they are easier to simulate.

After the DECI funded project, the newly established EC4aPDEs network will continue to recruit new members, with the aim of developing and sharing a common application software infrastructure that will make use of future European extreme computing resources.


The project has been granted access to 4 different machines on the DEISA Grid. The main features of these machines are outlined in the table below.

Name Architecture Location User Guide GSISSH Service Name Login
Mare Nostrum IBM Power PC, 10240 processors Barcelona Supercomputing Center, Spain Mare Nostrum User Guide bsc SSH - Send BSC SSH public key
SP6 IBM Power6-575, 5376 cores CINECA, Italy SP6 User Guide cineca GSISSH
Laki Intel Xeon X5570, 5600 cores, 32 Tesla nodes HLRS, Stuttgart, Germany Laki User Guide hlrs SSH - Send HLRS fixed IP address
Genius IBM BlueGene/P with 16,384 cores (development only) RZG, Germany Genius User Guide rzg GSISSH

Getting Started

  • Apply for an eScience Certificate and install it in a web browser.
  • Apply for a HECToR account for use with DEISA. Accounts with other HECToR projects are not valid.
  • Send DEISA the DN associated with your eScience Certificate.
  • Download GSISSH-Term from the correct location.
  • In GSISSH-Term login to a "door" system on the DEISA Grid. The default "door" system built into the DEISA version of GSISSH works.
  • From the "door" system, login to a DEISA machine listed above.
    • First load the DEISA environment on the "door" system. Type:
      module load deisa globus
    • Then use command line GSISSH to login. Type:
      gsissh $(deisa_service -i -s cineca)
  • To transfer files from your desktop to DEISA, use FTP tool provided in GSISSH-TERM. This enables you to transfer files to the "door" system only.
  • To transfer files from the "door" system to the "production" system, follow the example:
    globus-url-copy -vb file:///gpfs/h05//
    gsiftp://$(deisa_service -i -f cineca)/sp6/userdeisa//

If you are a member of the project, you may contact Lee Margetts for further information.


This project is funded from June 2010 to July 2011 under DECI-6, the DEISA Extreme Computing Initiative, through the DEISA Consortium, which is co-funded through the EU FP6 project RI-031513 and the FP7 project RI-222919.


  • Dr Lee Margetts, University of Manchester, UK (PI)
  • Dr Paul Mummery, University of Manchester, UK
  • Professor Stephane Bordas, University of Cardiff, UK
  • Professor Timon Rabczuk, University of Weimar, Germany
  • Professor Oubay Hassan MBE, University of Swansea, UK
  • Professor Guillaume Housieaux, Barcelona Supercomputing Center, Spain
  • Professor Marc Duflot, Cenaero, Belgium