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Register a new userAir shower simulation using {sc geant4} and commodity parallel computing
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We present an evaluation of a simulated cosmic ray shower, based on {sc geant4} and {sc top-c}, which tracks all the particles in the shower. {sc top-c} (Task Oriented Parallel C) provides a framework for parallel algorithm development which makes tractable the problem of following each particle. This method is compared with a simulation program which employs the Hillas thinning algorithm.
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{sc top-c} (Task Oriented Parallel C) is a freely available package for parallel computing. It is designed to be easy to learn and to have good tolerance for the high latencies that are common in commodity networks of computers. It has been successfully used in a wide range of examples, providing linear speedup with the number of computers. A brief overview of {sc top-c} is provided, along with recent experience with cosmic ray physics simulations.
The aim of this report of the Working Group on Hadronic Interactions and Air Shower Simulation is to give an overview of the status of the field, emphasizing open questions and a comparison of relevant results of the different experiments. It is shown that an approximate overall understanding of extensive air showers and the corresponding hadronic interactions has been reached. The simulations provide a qualitative description of the bulk of the air shower observables. Discrepancies are however found when the correlation between measurements of the longitudinal shower profile are compared to that of the lateral particle distributions at ground. The report concludes with a list of important problems that should be addressed to make progress in understanding hadronic interactions and, hence, improve the reliability of air shower simulations.
The radio detection method for cosmic rays relies on coherent emission from electrons and positrons which is beamed in a narrow cone along the shower axis. Currently the only mod- els to reproduce this emission with sufficient accuracy are Monte Carlo based simulations of the particle and radio emission physics, which require large investments of computation time. The work presented here focuses on condensing the simulation results into a semi-analytical model. This relies on building a framework based on theoretical predictions of radio emission, but instead of calculating the radio signal directly these models are used to map template simu- lations to the specifications of a given radio event. Our current approach slices the radio signal based on atmospheric depth of origin and weights these slices based on a shower parameter such as electron number or an effective dipole moment. One significant gain over the existing Monte Carlo codes lies in the fact this makes the depth of the shower maximum a direct input to the simulation where currently one has to pre-select showers based on their random number seed. Such a model has great potential for heavily simulation-based analysis methods, for example the LOFAR air shower reconstruction. These techniques are severely limited by the available computation time but have the lowest errors in real measurement applications.
The influence of the geomagnetic field on the development of air showers is studied. The well known International Geomagnetic Reference Field was included in the AIRES air shower simulation program as an auxiliary tool to allow calculating very accurate estimations of the geomagnetic field given the geographic coordinates, altitude above sea level and date of a given event. Some test simulations made for representative cases indicate that some quantities like the lateral distribution of muons experiment significant modifications when the geomagnetic field is taken into account.
The development of cost-effective highperformance parallel computing on multi-processor supercomputers makes it attractive to port excessively time consuming simulation software from personal computers (PC) to super computes. The power distribution system simulator (PDSS) takes a bottom-up approach and simulates load at the appliance level, where detailed thermal models for appliances are used. This approach works well for a small power distribution system consisting of a few thousand appliances. When the number of appliances increases, the simulation uses up the PC memory and its runtime increases to a point where the approach is no longer feasible to model a practical large power distribution system. This paper presents an effort made to port a PC-based power distribution system simulator to a 128-processor shared-memory supercomputer. The paper offers an overview of the parallel computing environment and a description of the modification made to the PDSS model. The performance of the PDSS running on a standalone PC and on the supercomputer is compared. Future research direction of utilizing parallel computing in the power distribution system simulation is also addressed.
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