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Register a new userLoad management strategy for Particle-In-Cell simulations in high energy particle acceleration
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In the wake of the intense effort made for the experimental CILEX project, numerical simulation cam- paigns have been carried out in order to finalize the design of the facility and to identify optimal laser and plasma parameters. These simulations bring, of course, important insight into the fundamental physics at play. As a by-product, they also characterize the quality of our theoretical and numerical models. In this paper, we compare the results given by different codes and point out algorithmic lim- itations both in terms of physical accuracy and computational performances. These limitations are illu- strated in the context of electron laser wakefield acceleration (LWFA). The main limitation we identify in state-of-the-art Particle-In-Cell (PIC) codes is computational load imbalance. We propose an innovative algorithm to deal with this specific issue as well as milestones towards a modern, accurate high-per- formance PIC code for high energy particle acceleration.
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We present a load balancing strategy for hybrid particle-mesh methods that is based on domain decomposition and element-local time measurement. This new strategy is compared to our previous approach, which assumes a constant weighting factor for each particle to determine the computational load. The timer-based load balancing is applied to a plasma expansion simulation. The performance of the new algorithm is compared to results presented in the past and a significant improvement in terms of computational efficiency is shown.
When a charged particle moves through a plasma at a speed much higher than the thermal velocity of the plasma, it is subjected to the force of the electrostatic field induced in the plasma by itself and loses its energy. This process is well-known as the stopping power of a plasma. In this paper we show that the same process works in particle-in-cell (PIC) simulations as well and the energy loss rate of fast particles due to this process is mainly determined by the number of plasma electrons contained in the electron skin depth volume. However, since there are generally very few particles in that volume in PIC simulations compared with real plasmas, the energy loss effect can be exaggerated significantly and can affect the results. Therefore, especially for the simulations that investigate the particle acceleration processes, the number of particles used in the simulations should be chosen large enough to avoid this artificial energy loss.
Furthering our understanding of many of todays interesting problems in plasma physics---including plasma based acceleration and magnetic reconnection with pair production due to quantum electrodynamic effects---requires large-scale kinetic simulations using particle-in-cell (PIC) codes. However, these simulations are extremely demanding, requiring that contemporary PIC codes be designed to efficiently use a new fleet of exascale computing architectures. To this end, the key issue of parallel load balance across computational nodes must be addressed. We discuss the implementation of dynamic load balancing by dividing the simulation space into many small, self-contained regions or tiles, along with shared-memory (e.g., OpenMP) parallelism both over many tiles and within single tiles. The load balancing algorithm can be used with three different topologies, including two space-filling curves. We tested this implementation in the code OSIRIS and show low overhead and improved scalability with OpenMP thread number on simulations with both uniform load and severe load imbalance. Compared to other load-balancing techniques, our algorithm gives order-of-magnitude improvement in parallel scalability for simulations with severe load imbalance issues.
The recently developed energy conserving semi-implicit method (ECsim) for PIC simulation is applied to multiple scale problems where the electron-scale physics needs to be only partially retained and the interest is on the macroscopic or ion-scale processes. Unlike hybrid methods, the ECsim is capable of providing kinetic electron information, such as wave-electron interaction (Landau damping or cyclotron resonance) and non-Maxwellian electron velocity distributions. However, like hybrid, the ECsim does not need to resolve all electron scales, allowing time steps and grid spacing orders of magnitude larger than in explicit PIC schemes. The additional advantage of the ECsim is that the stability at large scale is obtained while conserving energy exactly. Three examples are presented: ion acoustic waves, electron acoustic instability and reconnection processes.
We construct Boris-type schemes for integrating the motion of charged particles in particle-in-cell (PIC) simulation. The new solvers virtually combine the 2-step Boris procedure arbitrary n times in the Lorentz-force part, and therefore we call them the multiple Boris solvers. Using Chebyshev polynomials, a one-step form of the new solvers is provided. The new solvers give n^2 times smaller errors, allow larger timesteps, and have a long-term stability. We present numerical tests of the new solvers, in comparison with other particle integrators.
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