Efficient Large-Scale Coating Microstructure Formation Using Realistic CFD Models

Efficient Model Synchronization of Large-Scale Models

Realistic Large-Scale Network Optimisation

This paper considers communication network design problems that arise in the real world, with large numbers of nodes and link and switch costs dependent upon their traffic capacity. Such costs, in turn, depend upon network topology so are not fixed at the start of, or through, any optimisation process. Realistic topological restrictions are also discussed. The limitations of conventional approa...

COMPUTATIONALLY EFFICIENT OPTIMUM DESIGN OF LARGE SCALE STEEL FRAMES

Computational cost of metaheuristic based optimum design algorithms grows excessively with structure size. This results in computational inefficiency of modern metaheuristic algorithms in tackling optimum design problems of large scale structural systems. This paper attempts to provide a computationally efficient optimization tool for optimum design of large scale steel frame structures to AISC...

Darwini: Generating realistic large-scale social graphs

Synthetic graph generators facilitate research in graph algorithms and processing systems by providing access to data, for instance, graphs resembling social networks, while circumventing privacy and security concerns. Nevertheless, their practical value lies in their ability to capture important metrics of real graphs, such as degree distribution and clustering properties. Graph generators mus...

Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models

Training conditional maximum entropy models on massive data sets requires significant computational resources. We examine three common distributed training methods for conditional maxent: a distributed gradient computation method, a majority vote method, and a mixture weight method. We analyze and compare the CPU and network time complexity of each of these methods and present a theoretical ana...