Investigating scaling behaviour of monte carlo codes for dense matrix inversion

With the latest developments in the area of advanced computer architectures, we are already seeing large-scale machines at petascale level and are faced with the exascale computing challenge. All these require scalability at system, algorithmic and mathematical model level. In particular, efficient scalable algorithms are required to bridge the performance gap. Being able to predict application demeanour, performance and scalability of currently used software on new supercomputers of different architectures, varying sizes, and utilising alternative ways of intercommunication, can be of great benefit for researchers as well as application developers. This paper is concerned with scaling characteristics of Monte Carlo based algorithms for matrix inversion. The algorithmic behaviour on large-scale systems will be predicted with the help of an extreme-scale high-performance computing (HPC) simulator.