Parallelization of monte Carlo simulations and submission to a grid environment

presentation L. Maign

A perspective on the Healthgrid initiative

This paper presents a perspective on the Healthgrid initiative which involves European projects deploying pioneering applications of grid technology in the health sector. In the last couple of years, several grid projects have been funded on health related issues at national and European levels. A crucial issue is to maximize their cross fertilization in the context of an environment where data of medical interest can be stored and made easily available to the different actors in healthcare, physicians, healthcare centres and administrations, and of course the citizens. The Healthgrid initiative, represented by the Healthgrid association (http://www.healthgrid.org), was initiated to bring the necessary long term continuity, to reinforce and promote awareness of the possibilities and advantages linked to the deployment of GRID technologies in health. Technologies to address the specific requirements for medical applications are under development. Results from the DataGrid and other projects are given as examples of early applications.Comment: 6 pages, 1 figure. Accepted by the Second International Workshop on Biomedical Computations on the Grid, at the 4th IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGrid 2004). Chicago USA, April 200

GATE simulation for medical physics with genius Web portal

présenté par C. ThiamPCSV team of the LPC laboratory in Clermont-Ferrand is involved in the deployment of biomedical applications on the grid architecture. One of these applications deals with the deployment of GATE (Geant4 Application for Tomographic Emission) for medical physics application. The aim of the developments actually performed is to enable an application of the GATE platform in clinical routine. However, this perspective is only possible if the computing time and user time are highly reduced. The new grid architecture, developed within the framework of the European project Enabling Grid for E-sciencE (EGEE) is there to answer this requirement. The use of the grid resources must be transparent easy and rapid for the medical physicists. For this perpose, we adapted the GENIUS web portal in order to facilitate the GATE simulations planning on the grid. We will present a demonstration of the GENIUS portal which integrates all the functionalities of EGEE: to create, to submit and manage GATE jobs on the grid architecture. Our GATE activities for dosimetry application entered in to direct phase of evaluation by the cancer treatment center of Clermont Ferrand (Centre Jean perrin).A work station is currently available in this center to test the use of GATE application on the grid through GENIUS. This portal will allow in a long term to use GATE application in brachytherapy and radiotherapy treatment planning using medical data (medical images, DICOM, binary data dose calculation in the heterogeneous mediums) and to analyze the results obtained in visual form. Other functionalities are under development and will make possible to register medical data on grid storages elements and to manage them. However, these data must be anonymised before their recording on the grid. Their access via the GENIUS portal must be made safe and fast (compared simulation computing time). In order to be sure that the medical data are accessible for calculations, their replication on various storage element (SE) should be possible. The grid services give the possibility of managing this information in a free way and transparently. Operations of data handling and catalogues on the grid are ensured by the Replica Manager system which integrates all tools making it possible to manage data on the grid. The computing grid give promising results and meet a definite need: reach acceptable computing time for a future use of Monte Carlo simulations for treatment planning in brachytherapy and radiotherapy

Les grilles de calcul au service de la physique médicale

présenté par C.O. Thiam, proceedings sous forme de CDLes Simulations Monte Carlo GATE en radiothérapie nécessitent plusieurs heures de calculs. En effet, un résultat précis ne peut être obtenu qu'en générant beaucoup d'événements. Nous étudions donc les capacités des grilles de calcul notamment en terme de réduction des temps de calculs, et les services qu'elles offrent pour une utilisation future en milieu médical. Cette infrastructure, s'inscrit dans le cadre du projet européen EGEE. Ce projet consiste à mutualiser des ressources réparties sur différentes sites afin de pouvoir accéder à de la puissance de calcul, à des données partagées et de bénéficier d'une continuité de service

Monte Carlo Simulation With The GATE Software Using Grid Computing

DémonstrationInternational audienceMonte Carlo simulations needing many replicates to obtain good statistical results can be easily executed in parallel using the "Multiple Replications In Parallel" approach. However, several precautions have to be taken in the generation of the parallel streams of pseudo-random numbers. In this paper, we present the distribution of Monte Carlo simulations performed with the GATE software using local clusters and grid computing. We obtained very convincing results with this large medical application, thanks to the EGEE Grid (Enabling Grid for E-sciencE), achieving in one week computations that could have taken more than 3 years of processing on a single computer. This work has been achieved thanks to a generic object-oriented toolbox called DistMe which we designed to automate this kind of parallelization for Monte Carlo simulations. This toolbox, written in Java is freely available on SourceForge and helped to ensure a rigorous distribution of pseudo-random number streams. It is based on the use of a documented XML format for random numbers generators statuses

Grid technology for biomedical applications

International audienceThe deployment of biomedical applications in a grid environment has started about three years ago in several European projects and national ini-tiatives. These applications have demonstrated that the grid paradigm was rele-vant to the needs of the biomedical community. They have also highlighted that this community had very specific requirements on middleware and needed fur-ther structuring in large collaborations in order to participate to the deployment of grid infrastructures in the coming years. In this paper, we propose several ar-eas where grid technology can today improve research and healthcare. A cru-cial issue is to maximize the cross fertilization among projects in the perspec-tive of an environment where data of medical interest can be stored and made easily available to the different actors of healthcare, the physicians, the health-care centres and administrations, and of course the citizens

Pseudo-Random Streams for Distributed and Parallel Stochastic Simulations on GP-GPU

International audienceRandom number generation is a key element of stochastic simulations. It has been widely studied for sequential applications purposes, enabling us to reliably use pseudo-random numbers in this case. Unfortunately, we cannot be so enthusiastic when dealing with parallel stochastic simulations. Many applications still neglect random stream parallelization, leading to potentially biased results. In particular parallel execution platforms, such as Graphics Processing Units (GPUs), add their constraints to those of Pseudo-Random Number Generators (PRNGs) used in parallel. This results in a situation where potential biases can be combined with performance drops when parallelization of random streams has not been carried out rigorously. Here, we propose criteria guiding the design of good GPU-enabled PRNGs. We enhance our comments with a study of the techniques aiming to parallelize random streams correctly, in the context of GPU-enabled stochastic simulations

Monte Carlo validation of a mu-SPECT imaging system on the lightweight grid CiGri

à paraître dans Future Generation Computer SystemsMonte Carlo Simulations (MCS) are nowadays widely used in the field of nuclear medicine for system and algorithms designs. They are valuable for accurately reproducing experimental data, but at the expense of a long computing time. An efficient solution for shorter elapsed time has recently been proposed: grid computing. The aim of this work is to validate a small animal gamma camera MCS and to confirm the usefulness of grid computing for such a study. Good matches between measured and simulated data were achieved and a crunching factor up to 70 was attained on a lightweight campus grid

Distribution of Random Streams for Simulation Practitioners

International audienceThere is an increasing interest in the distribution of parallel random number streamsin the high-performance computing community particularly, with the manycore shift. Even ifwe have at our disposal statistically sound random number generators according to the latestand thorough testing libraries, their parallelization can still be a delicate problem. Indeed, aset of recent publications shows it still has to be mastered by the scientific community. Withthe arrival of multi-core and manycore processor architectures on the scientist desktop, modelerswho are non-specialists in parallelizing stochastic simulations need help and advice in distributingrigorously their experimental plans and replications according to the state of the art in pseudo-random numbers parallelization techniques. In this paper, we discuss the different partitioningtechniques currently in use to provide independent streams with their corresponding software. Inaddition to the classical approaches in use to parallelize stochastic simulations on regular processors,this paper also presents recent advances in pseudo-random number generation for general-purposegraphical processing units. The state of the art given in this paper is written for simulationpractitioners