Abstract
Geant4 is a software toolkit for the simulation of the passage of particles through matter. It is used by a large number of experiments and projects in a variety of application domains, including high energy physics, astrophysics and space science, medical physics and radiation protection. Over the past several years, major changes have been made to the toolkit in order to accommodate the needs of these user communities, and to efficiently exploit the growth of computing power made available by advances in technology. The adaptation of Geant4 to multithreading, advances in physics, detector modeling and visualization, extensions to the toolkit, including biasing and reverse Monte Carlo, and tools for physics and release validation are discussed here.
Highlights
Introduction A key component ofGEANT4 is the geometry modeler [11], which provides a wide variety of tools and solutions for describing geometry setups from simple to highly complex
In this design the memory savings are obtained by sharing among all the threads the key data which are constant during simulation: the geometry description and the tables used by electromagnetic physics processes [2]
The most interesting particles are electrons and hadrons at high energy because they exercise the majority of physics models used in high energy parameterized (HEP) simulations of full showers
Summary
Pandia Oy, Hiomotie 10, 5th floor, 00380 Helsinki, Finland. 3 Current address: Translational and Molecular Imaging Institute, Icahn School of Medicine at Mt. Advances in memory technology have not kept pace and the amount of memory available per CPU cycle has decreased These trends have led to a re-examination of some of the basic assumptions of simulation computing, and to the evolution of the GEANT4 simulation toolkit. Common to most these domains, but especially true for high energy physics, is the demand for increasingly detailed geometries and more sophisticated physical models This in turn drives the need for more CPU cycles, and the relative decrease of memory drives the need for more efficient memory management. In the usual computer science sense, it refers to an instance of an application which is being executed This is the meaning assumed in the discussion of multithreading.
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