Mesoscale simulations have grown recently in importance due to their capacity of capturing molecular and atomistic effects without having to solve for a prohibitively large number of particles needed in Molecular Dynamic (MD) simulations. Different approaches, emerging from a coarse approximation to a group of atoms and molecules, allow reproducing both chemical and physical main properties as well as continuum behaviour such as the hydrodynamics of fluid flows.
One of the most common techniques is the Dissipative Particle Dynamics (DPD): an approximate, coarse-grain, mesoscale simulation method for investigating phenomena between the atomic and the continuum scale world, like flows through complex geometries, micro fluids, phase behaviours and polymer processing. It consists of an off-lattice, discrete particle method similar to MD but with replacement of a soft potential for the conservative force, a random force to simulate the Brownian motion of the particles and a drag force to balance the random force and conserve the total momentum of the system.
However, real applications usually consist of a large number of particles and despite the coarse grain approximation, compared to MD, High Performance Computing (HPC) is often required for simulating systems of industrial and scientific interest. On the other hand, today’s hardware is quickly moving towards hybrid CPU-GPU architectures. In fact, five of the top ten supercomputer are made of mixed CPU and NVidia GPU accelerators which allow to achieve hundreds of PetaFlops performance. This type of architecture is also one of the main paths toward Exascale.
Few software, like DL_MESO, userMESO and LAMMPS, can currently simulate large DPD simulations. In particular, DL_MESO has recently been ported to multi-GPU architectures and runs efficiently up to 4096 GPUs. This allows investigating very large system with billions of particles within affordable computational effort. However, additional effort is required to enable the current version to cover more complex physics, like long range forces as well as achieving higher parallel computing efficiency.
The purpose of this proposal is to organize an Extended Software Development Workshop (ESDW) to introduce students to the parallel programming of hybrid CPU-GPU systems. The intention is not only to port mesoscale solvers on GPUs, but also to expose the ECAM community to this new programming paradigm and to benefit from it also in the other Work Packages. The course will then be open to all ECAM postdocs. Many users of DL_MESO are based at Daresbury Laboratory and we expect a good participation from local researchers. Moreover, due to DL_MESO’s large use in industrial research, we expect potential students from industrial companies like Unilever, Syngenta and Infineum to attend.