On the parallelization of multipacting simulation codes for the design of particle accelerator components

Particle trajectory and collision simulation is a critical step of the design and construction of novel particle accelerator components. However it requires a huge computational effort which can slow down the design process. We started from a sequential simulation program which is used to study an event called Multipacting. Our work explains the physical problem that is simulated and the implications it can have on the behavior of the components. Then we analyze the original program’s operation to find the best options for parallelization. We first developed a parallel version of the Multipacting simulation and were able to accelerate the execution up to \(\sim 35\times \) $\sim 35\times$ with 48 or 56 cores. In the best cases, parallelization efficiency was maintained up to 16 cores ( \(\sim 95\) $\sim 95$ %) and the speed-up plateaus at around 40–48 cores. When this first parallelization effort was tried for multi-power simulations, we found that parallelism was severely limited with a maximum of \(20\times \) $20\times$ speed-up. For this reason, we introduced a new method to improve the parallelization efficiency for this second use case. This method uses a shared processor pool for all simulations of electrons (OnePool). OnePool improved scalability by pushing the speed-up to over \(32\times \) $32\times$ .