We have created a scalable implementation of the kinetic Monte-Carlo method, SPOCK (Scalable Parallel Optimistic Crystal Kinetics). Unlike most reported parallel implementations relying on approximation to achieve parallelism, our parallelization is exact and accomplished using the Time Warp paradigm. We demonstrate that our implementation exhibits near perfect scaling for two different and important classes of systems. It runs efficiently on Vulcan, a 24 thousand node BlueGene/Q machine, using all ~400 thousand cores and ~1.6 million MPI tasks. Further, we have run production simulations using the full Vulcan machine and requiring nearly all available system memory. In this paper we demonstrate these results, and discuss some important implementation details. The kinetic Monte-Carlo method is ubiquitous within the natural sciences, and important classes of problems have so far been limited to sequential simulation. For many scientific simulations, an exact parallel implementation of the kinetic Monte-Carlo method has the potential of being game changing.

Blue Gene/L represents a new way to build supercomputers, using a large number of low power processors, together with multiple integrated interconnection networks. Whether real applications can scale to tens of thousands of processors (on a machine like Blue Gene/L) has been an open question. In this paper, we describe early experience with several physics and material science applications on a 32,768 node Blue Gene/L system, which was installed recently at the Lawrence Livermore National Laboratory. Our study shows some problems in the applications and in the current software implementation, but overall, excellent scaling of these applications to 32K nodes on the current Blue Gene/L system. While there is clearly room for improvement, these results represent the first proof point that MPI applications can effectively scale to over ten thousand processors. They also validate the scalability of the hardware and software architecture of Blue Gene/L.

We describe an innovative highly parallel application program, ParaDiS, which computes the plastic strength of materials by tracing the evolution of dislocation lines over time. We discuss the issues of scaling the code to tens of thousands of processors, and present early scaling results of the code run on a prototype of the BlueGene/L supercomputer being developed by IBM in partnership with the US DOE’s ASC program.