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GRNET signed contract for the development of Greece’s National HPC infrastructure

Ημερομηνία: 
04/07/2014

The Greek Research and Technology Network (GRNET) pioneers in the field of supercomputing infrastructures, by proceeding to the development of Greece’s first national high-performance computing system (HPC) to support large-scale scientific applications. The supply and installation of the new system was assigned to COSMOS Business Systems in collaboration with IBM, after an open international tender, which was carried out by GRNET. The new infrastructure is expected to play an important role in the development and promotion of scientific research in the country and in South East Europe.

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New case study: Tracking a biomarker for Alzheimer’s disease

How the grid can be used to test the software packages tracking a diagnostic biomarker for Alzheimer’s disease.

Alzheimer’s disease starts slowly and patients may not show symptoms for many years. Yet subtle physical changes will already be occurring, as their brain cells begin to die and the brain itself atrophies. The key to early diagnosis is to find a reliable ‘biomarker’ for Alzheimer’s that researchers can track, in order to monitor the disease and decide on treatments. But how can they identify a reliable biomarker from brain scan images?
One useful clue is the volume of the hippocampus - the region in the brain associated with memory that starts to shrink at the onset of Alzheimer’s. Many software programs have been developed to measure changes in hippocampus size from imaging scans. Now researchers at Vrije Universiteit Amsterdam have used grid computing to compare the performance of several software programs by analysing thousands of MRI scans taken from Alzheimer’s patients.
The study produced a valuable benchmark to evaluate and monitor Alzheimer’s biomarkers. Better biomarkers from brain scan data open the door to earlier diagnosis, effective monitoring, and being able to quickly test new drugs for Alzheimer’s.

Brain with Alzheimer's diseaseIllustration showing a brain at the preclinical stage of Alzheimer's disease, highlighting the location of the hippocampus. 

Deciphering MRI data

Alzheimer’s disease kills brain cells and causes the brain to atrophy and shrink. As the disease progresses, patients begin to experience memory loss and inability to carry out physical tasks. The diagnosis is usually made on the basis of these symptoms and the challenge is to distinguish between the normal signs of aging and the beginning of Alzheimer’s.

One way to tell normal aging from actual symptoms is to look for the visual signs of Alzheimer’s disease – the biomarkers of Alzheimer’s. The volume of the hippocampus, one of the first regions to suffer as the disease develops, is one of these biomarkers.  Doctors can use a variety of different software programs to measure hippocampus shrinkage from MRI scans. They are computing intensive and may take several days to run on each scan.

Keith Cover, a physicist working at VU University Medical Center (VUmc) in Amsterdam, tested the reliability of several hippocampal shrinkage software packages. This involved analysing approximately 3,300 MRI scans from over 600 patients many times each, requiring many core-years of computation.

The brain scans were collected during the Alzheimer’s Disease Neuroimaging Initiative (ADNI) study, which began in 2004. Each patient provided two back-to-back scans in every visit. This allowed the team to look at two sets of what should be identical data and check how reliable each software package is.

Computing with neuGRID

Software packages FSL and FreeSurfer are widely used in Alzheimer’s research and consume a lot of computational power to piece together data from hundreds of patients. For this study, Keith and his team used the neuGRID - a leading European e-infrastructure for the neuroscience research community.

Through the neuGRID platform, researchers can analyse and share brain scan datasets, use medical software tools and benefit from specialised support.

neuGRID was originally established in 2008. Now, the EU-funded N4U project, led by Giovanni Frisoni, has expanded neuGRID through collaborations with several partners, including EGI, which have provided access to public grid computing resources via the Alternative Energies and Atomic Energy Commission (CEA) and Hellasgrid, the NGI of Greece.

With neuGRID, the calculations for Keith’s study were processed in weeks, instead of years.

“A modern trial could have 100 to 1,000 patients providing these scans,” Keith explained. “Most laboratories have their own MRI scanners but few have their own clusters and the expertise to use them, so they don’t have the computational power to carry out the data analysis. With grid computing, thousands of scans can be processed in a trivial time, days instead of years.”

Thanks to neuGRID, university groups can carry out their own studies, then make use of grid resources to analyse the data.

Comparing Analyses

The study was able to show that FSL and FreeSurfer analyses of hippocampal atrophy rates are similar, while noting slight differences in the current versions of the programs.

With the speed of analysis brought by grid computing, the hippocampus biomarker can be used more widely to help diagnose and monitor individual patients. Until now, this biomarker has only been looked at on averages over groups and clinical trials.

The study has also demonstrated that the ADNI data provides a reliable benchmark that could be used to compare the performance of other similar software packages.

Keith is already looking towards the future: “Now that we’ve got this benchmark in place, we’re now looking at different algorithms and hoping to see if someone has come up with something better.”

The importance of GRID computing in the investigation of climate

Climate change is unequivocal, as is evident from observations of increases in global average air and ocean temperatures, widespread melting of snow and ice and rising global average sea level (IPCC, 2007). Since climate change is concerned with important societal issues, it is very important to assess impacts of climate change already underway and address adaptation strategies to reduce vulnerability and risks of climate change.

Climate models use mathematics and the laws of physics to simulate the interactions of the basic components of the climate system. Differential equations are used to relate fundamental physical quantities (e.g. temperature, pressure, wind etc) to each other.  Each equation is solved at discrete grid points on the earth’s surface, at a fixed time interval (time-step) and several vertical layers, defined by the regular three-dimensional grid. Horizontal resolutions of global climate models range between 100-200 Km while of regional climate models from 10 to 50 Km.

In the Department of Meteorology and Climatology at the Aristotle University of Thessaloniki high resolution (10 Km) transient (1961-2050) climatic simulations were performed over South Eastern Europe with the regional climate model RegCM3 (http://gforge.ictp.it/gf/project/regcm/) using the HellasGrid resources within the framework of the ongoing project Geoclima.

The simulations were performed under the IPCC A1B scenario (http://www.ipcc.ch/ipccreports/tar/wg1/029.htm). Projected near-surface temperatures staring from present climate until the middle of the 21st century are shown in Figure 1. 

image001

Figure 1 – Evolution (1961-2050) of near-surface temperature over South Eastern Europe simulated in AUTH using the Hellas-Grid computational resources

The final aim of Geoclima (www.geoclima.eu) project is to develop a Geographical Information System (GIS) allowing the user to visualize, manage and analyze the information which is directly or indirectly related to climate and its future projections over SE Europe. 

Contact details: 

  • H. Feidas (PI), Associate Professor, AUTH, hfeidas (at) geo.auth.gr

  • P. Zanis, Assistant Professor, AUTH, zanis (at) geo.auth.gr

  • E. Katragkou, Lecturer, AUTH, katragou (at) auth.gr

  • Scientific Computing Center, AUTH, contact (at) grid.auth.gr

References

  1. IPCC, 2007: Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, Pachauri, R.K and Reisinger, A. (eds.)]. IPCC, Geneva, Switzerland, 104 pp.

Η λέκτορας κα. Ελένη Κατράγκου μιλάει στο EGI Community Forum

Η Λέκτορας του τμ. Γεωλογίας κα. Ελένη Κατράγκου, EGI Champion, μιλά στο EGI Community Forum 2013, στο Manchester για την έρευνά της. Το Grid Computing όπως αναφέρει είναι ιδιαιτέρως σημαντικό γιατί παρέχει στους ερευνητές τους απαραίτητους υπολογιστικούς και αποθηκευτικούς πόρους, καθώς και την τεχνική βοήθεια για να εκτελέσουν περίπλοκες και μακροπρόθεσμες κλιματικές προσομοιώσεις.
Σύμφωνα με την κυρία Κατράγκου, το Grid Computing διευκολύνει την υποκλιμάκωση των προσομοιώσεων από ένα παγκόσμιο σε ένα τοπικό επίπεδο. Τα υψηλής ανάλυσης δεδομένα χρησιμοποιούνται σε στρατηγικές προσαρμογής και στην διαχείριση ρίσκου που σχετίζονται την κλιματική αλλαγή και έχουν ιδιαίτερες επιπτώσεις στην κοινωνία. Παροτρύνει τους ερευνητές να έρθουν σε επαφή με το EGI και τις παρεχόμενες υπηρεσίες για να βελτιώσουν την δουλειά τους.

Introducing our three new Champions

EGI is pleased to announce that another three brilliant scientists have joined our Champion network.

EGI Champions are enthusiastic researchers who use EGI computing resources for their work and are keen to liaise with research communities to spread the word about the benefits of grid computing to science.

Our new champions are:

  • Afonso Duarte, a biophysicist based at ITQB in Portugal, where he uses NMR spectroscopy and protein modelling to understand how solutes are transported through cell membranes. He is a Marie Curie Fellow.

  • Fotis Psomopoulos, a computer scientist based at the Centre for Research & Technology Hellas with an interest on large scale analysis of biological data and data-mining algorithms.

  • and Joeri van Leeuwen, an astronomer involved in the Low Frequency Array (LOFAR) experiment in the Netherlands.

SEE-VO software

Currently the following free licenced software has been installed at the HellasGrid sites serving the South Eastern Europe virtual organization (SEE-VO). For each software is given its name, the tag with which it is published by every site, its official site and a guide on how to use it. Regional users who are members of the SEE-VO may request tha installation of additional software in the SEE-VO sites, by sending a request to the HellasGrid Application Support Team

Software Name Software Tag Software Site How to use it
Quantum Espresso VO-see-Espresso R1 
Fluka VO-see-FLUKA-2008.3.7 R2
HYDRA VO-see-HYDRA-CLIENT R3 G3
R (Statistics) VO-see-R-2.9.2 R4
RNAhybrid  VO-see-RNAHybrid-2.1 R5 G5
GNU Scientific Library VO-see-gsl-1.9 R6 G6
MEEP VO-see-meep R7 G7
Octave VO-see-octave-2.1.73 R8 G8
Sun JDK VO-see-sunjdk1.6.0_04 R9 G9
RegCM VO-see-RegCM R10
Geant4 VO-see-geant4.9.5 R11 G11
Root VO-see-root-5.34.02 R12 G12
OpenFOAM VO-see-OpenFOAM R13
GFORTRAN GFORTRAN R14
GFORTRAN-4.1 GFORTRAN-4.1 R15
GFORTRAN-4.4 GFORTRAN-4.4 R16
GNUPLOT GNUPLOT R17
MEGAlib VO-see-MEGAlib R18 G18

Also at every site other software packages have been installed concerning other VOs, like atlas, cms, biomed, etc.

B-physics on the grid: a PhD student’s perspective

We have a new case study on our website!

This time, Serena Oggero, a PhD student at NIKHEF (The Netherlands), gives us a first-person acoount of what is it like to use grid computing. The case study - B-physics on the grid: the view from the front - describes Serena's research at the LHCb and the role the grid plays.

Here is how it starts:

If you ask “hey man, shall we go for a beer later?,” how many of your friends reply with something like: “maybe tomorrow, I really have to baby-sit my ntuples tonight”?

Welcome to the happy and slightly geeky particle physics community! Happy, because I think we are a species of truly fortunate people, despite our constant scepticism and restlessness. And most of us were already slightly geeky anyway, even before starting to baby-sit ntuples. [continue reading...]
 

Protecting Portugal’s Aveiro Lagoon

How grid computing allows for a better management of coastal resources.

The Aveiro Lagoon in Portugal is a national treasure. With a length of about 45km and separated from the Atlantic Ocean by a sandy dune barrier, this shallow lagoon is one of Europe’s last pristine coastal marshes and a haven for many bird species. The Ria de Aveiro, as it is known locally, is also an important source of revenue in the region, fuelling not only the tourism and aquaculture industries but also artisan fishing and the collection of fleur de sel, a prized variety of salt.
In the past few years the lagoon (technically a half-delta) has been threatened by a decrease in water quality due to industrial, urban and agricultural effluents, but thanks to the Ria’s economic, ecologic and cultural importance, there is a strong push to preserve its ecosystem. The key to long-term sustainability is efficient management and to achieve that, decision-makers need to have a solid understanding of this environment.

Marta Rodrigues and Anabela Oliveira, together with colleagues from National Laboratory for Civil Engineering, Portugal (LNEC), applied a three-dimensional computational model called ECO-SELFE to the Aveiro Lagoon scenario. ECO-SELFE is a fully-coupled ecological-hydrodynamic model. This means that it has modules that determine physical variables (e.g. currents, water temperature or salinity) alongside others for biochemical processes (e.g. carbon, nitrogen cycles) and even ecological relationships at the base of the food chain (e.g. plankton mortality or availability of prey). The idea was to determine how the different ecological input parameters are interconnected and which ones are the most likely to affect the model results and the health of the lake.

 

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