Speaker
Description
In HEP experiments CPU resources required by MC simulations are constantly growing and becoming a very large fraction of the total computing power (greater than 75%). At the same time the pace of performance improvements given by technology is slowing down, so the only solution is a more efficient use of resources. Efforts are ongoing in the LHC experiment collaborations to provide multiple options for simulating events in a faster way when higher statistics is needed. A key of the success for this strategy is the possibility of enabling these fast simulation options in a common framework with minimal action by the final user.
In this talk we will describe the solution adopted in Gauss, the LHCb simulation software framework, to selectively exclude particles from being simulated by the Geant4 toolkit and to insert the corresponding hits generated in a faster way. The approach, integrated within the Geant4 toolkit, has been applied to the LHCb calorimeter but it could also be used
for other subdetectors. The hits generation can be carried out by any external tool, e.g. by a static library of showers or more complex machine-learning techniques. A first implementation of the calorimeter hit generation will be described. Detailed timing measurements and a comparison with the default simulation for reference physical quantities will be also presented.
