117,653 research outputs found
Monte Carlo Simulation With The GATE Software Using Grid Computing
DĂ©monstrationInternational 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 Interoperation with ARC Middleware for the CMS Experiment
The Compact Muon Solenoid (CMS) is one of the general purpose experiments at the CERN Large Hadron Collider (LHC). CMS computing relies on different grid infrastructures to provide computational and storage resources. The major grid middleware stacks used for CMS computing are gLite, Open Science Grid (OSG) and ARC (Advanced Resource Connector). Helsinki Institute of Physics (HIP) hosts one of the Tier-2 centers for CMS computing. CMS Tier-2 centers operate software systems for data transfers (PhEDEx), Monte Carlo production (ProdAgent) and data analysis (CRAB). In order to provide the Tier-2 services for CMS, HIP uses tools and components from both ARC and gLite grid middleware stacks. Interoperation between grid systems is a challenging problem and HIP uses two different solutions to provide the needed services. The first solution is based on gLite-ARC grid level interoperability. This allows to use ARC resources in CMS without modifying the CMS application software. The second solution is based on developing specific ARC plugins in CMS software
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Speeding-up the execution of credit risk simulations using desktop grid computing: A case study
This paper describes a case study that was
undertaken at a leading European Investment
bank in which desktop grid computing was used
to speed-up the execution of Monte Carlo credit risk simulations. The credit risk simulations were modelled using commercial-off-the-shelf simulation packages (CSPs). The CSPs did not incorporate built-in support for desktop grids, and therefore the authors implemented a middleware for desktop grid computing, called WinGrid, and interfaced it with the CSP. The performance results show that WinGrid can speed-up the execution of CSP-based Monte Carlo simulations. However, since WinGrid was installed on non-dedicated PCs, the speed-up
achieved varied according to users’ PC usage.
Finally, the paper presents some lessons learnt from this case study. It is expected that this paper will encourage simulation practitioners and CSP vendors to experiment with desktop grid computing technologies with the objective of speeding-up simulation experimentation
SKIRT: the design of a suite of input models for Monte Carlo radiative transfer simulations
The Monte Carlo method is the most popular technique to perform radiative
transfer simulations in a general 3D geometry. The algorithms behind and
acceleration techniques for Monte Carlo radiative transfer are discussed
extensively in the literature, and many different Monte Carlo codes are
publicly available. On the contrary, the design of a suite of components that
can be used for the distribution of sources and sinks in radiative transfer
codes has received very little attention. The availability of such models, with
different degrees of complexity, has many benefits. For example, they can serve
as toy models to test new physical ingredients, or as parameterised models for
inverse radiative transfer fitting. For 3D Monte Carlo codes, this requires
algorithms to efficiently generate random positions from 3D density
distributions. We describe the design of a flexible suite of components for the
Monte Carlo radiative transfer code SKIRT. The design is based on a combination
of basic building blocks (which can be either analytical toy models or
numerical models defined on grids or a set of particles) and the extensive use
of decorators that combine and alter these building blocks to more complex
structures. For a number of decorators, e.g. those that add spiral structure or
clumpiness, we provide a detailed description of the algorithms that can be
used to generate random positions. Advantages of this decorator-based design
include code transparency, the avoidance of code duplication, and an increase
in code maintainability. Moreover, since decorators can be chained without
problems, very complex models can easily be constructed out of simple building
blocks. Finally, based on a number of test simulations, we demonstrate that our
design using customised random position generators is superior to a simpler
design based on a generic black-box random position generator.Comment: 15 pages, 4 figures, accepted for publication in Astronomy and
Computin
Lattice QCD Thermodynamics on the Grid
We describe how we have used simultaneously nodes of the
EGEE Grid, accumulating ca. 300 CPU-years in 2-3 months, to determine an
important property of Quantum Chromodynamics. We explain how Grid resources
were exploited efficiently and with ease, using user-level overlay based on
Ganga and DIANE tools above standard Grid software stack. Application-specific
scheduling and resource selection based on simple but powerful heuristics
allowed to improve efficiency of the processing to obtain desired scientific
results by a specified deadline. This is also a demonstration of combined use
of supercomputers, to calculate the initial state of the QCD system, and Grids,
to perform the subsequent massively distributed simulations. The QCD simulation
was performed on a lattice. Keeping the strange quark mass at
its physical value, we reduced the masses of the up and down quarks until,
under an increase of temperature, the system underwent a second-order phase
transition to a quark-gluon plasma. Then we measured the response of this
system to an increase in the quark density. We find that the transition is
smoothened rather than sharpened. If confirmed on a finer lattice, this finding
makes it unlikely for ongoing experimental searches to find a QCD critical
point at small chemical potential
The CMS Integration Grid Testbed
The CMS Integration Grid Testbed (IGT) comprises USCMS Tier-1 and Tier-2
hardware at the following sites: the California Institute of Technology, Fermi
National Accelerator Laboratory, the University of California at San Diego, and
the University of Florida at Gainesville. The IGT runs jobs using the Globus
Toolkit with a DAGMan and Condor-G front end. The virtual organization (VO) is
managed using VO management scripts from the European Data Grid (EDG). Gridwide
monitoring is accomplished using local tools such as Ganglia interfaced into
the Globus Metadata Directory Service (MDS) and the agent based Mona Lisa.
Domain specific software is packaged and installed using the Distrib ution
After Release (DAR) tool of CMS, while middleware under the auspices of the
Virtual Data Toolkit (VDT) is distributed using Pacman. During a continuo us
two month span in Fall of 2002, over 1 million official CMS GEANT based Monte
Carlo events were generated and returned to CERN for analysis while being
demonstrated at SC2002. In this paper, we describe the process that led to one
of the world's first continuously available, functioning grids.Comment: CHEP 2003 MOCT01
Path-tracing Monte Carlo Library for 3D Radiative Transfer in Highly Resolved Cloudy Atmospheres
Interactions between clouds and radiation are at the root of many
difficulties in numerically predicting future weather and climate and in
retrieving the state of the atmosphere from remote sensing observations. The
large range of issues related to these interactions, and in particular to
three-dimensional interactions, motivated the development of accurate radiative
tools able to compute all types of radiative metrics, from monochromatic, local
and directional observables, to integrated energetic quantities. In the
continuity of this community effort, we propose here an open-source library for
general use in Monte Carlo algorithms. This library is devoted to the
acceleration of path-tracing in complex data, typically high-resolution
large-domain grounds and clouds. The main algorithmic advances embedded in the
library are those related to the construction and traversal of hierarchical
grids accelerating the tracing of paths through heterogeneous fields in
null-collision (maximum cross-section) algorithms. We show that with these
hierarchical grids, the computing time is only weakly sensitivive to the
refinement of the volumetric data. The library is tested with a rendering
algorithm that produces synthetic images of cloud radiances. Two other examples
are given as illustrations, that are respectively used to analyse the
transmission of solar radiation under a cloud together with its sensitivity to
an optical parameter, and to assess a parametrization of 3D radiative effects
of clouds.Comment: Submitted to JAMES, revised and submitted again (this is v2
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