Performance analysis of heterogeneous multi-cluster systems

When building a cost-effective high-performance parallel processing system, a performance model is a useful tool for exploring the design space and examining various parameters. However, performance analysis in such systems has proven to be a challenging task that requires the innovative performance analysis tools and methods to keep up with the rapid evolution and ever increasing complexity of such systems. To this end, we propose an analytical model for heterogeneous multi-cluster systems. The model takes into account stochastic quantities as well as network heterogeneity in bandwidth and latency in each cluster. Also, blocking and non-blocking network architecture model is proposed and are used in performance analysis of the system. The message latency is used as the primary performance metric. The model is validated by constructing a set of simulators to simulate different types of clusters, and by comparing the modeled results with the simulated ones.

Study of growth mechanism of TiC cluster in ferrite via molecular dynamics simulation

Abstract Atomistic simulations were used to investigate the evolution process of titanium carbide clusters to mature precipitates in ferrite. The typical kinetic of carbide cluster growth was studied in detail through analyzing the atomic interactions of a carbide cluster with scattered carbon atoms. The driving force required for cluster growth was calculated along with the atomic diffusivity in the iron matrix, exploring the change in response as two main growth steps. The growth kinetic improved the understanding of precipitate evolution at the atomic level.