Spatial variability of flow statistics within regular building arrays

Turbulence statistics obtained by direct numerical simulations are analysed to investigate spatial heterogeneity within regular arrays of building-like cubical obstacles. Two different array layouts are studied, staggered and square, both at a packing density of λp=0.25 . The flow statistics analysed are mean streamwise velocity ( u− ), shear stress ( u′w′−−−− ), turbulent kinetic energy (k) and dispersive stress fraction ( u˜w˜ ). The spatial flow patterns and spatial distribution of these statistics in the two arrays are found to be very different. Local regions of high spatial variability are identified. The overall spatial variances of the statistics are shown to be generally very significant in comparison with their spatial averages within the arrays. Above the arrays the spatial variances as well as dispersive stresses decay rapidly to zero. The heterogeneity is explored further by separately considering six different flow regimes identified within the arrays, described here as: channelling region, constricted region, intersection region, building wake region, canyon region and front-recirculation region. It is found that the flow in the first three regions is relatively homogeneous, but that spatial variances in the latter three regions are large, especially in the building wake and canyon regions. The implication is that, in general, the flow immediately behind (and, to a lesser extent, in front of) a building is much more heterogeneous than elsewhere, even in the relatively dense arrays considered here. Most of the dispersive stress is concentrated in these regions. Considering the experimental difficulties of obtaining enough point measurements to form a representative spatial average, the error incurred by degrading the sampling resolution is investigated. It is found that a good estimate for both area and line averages can be obtained using a relatively small number of strategically located sampling points.

Evolving graphs: dynamical models, inverse problems and propagation

Applications such as neuroscience, telecommunication, online social networking, transport and retail trading give rise to connectivity patterns that change over time. In this work, we address the resulting need for network models and computational algorithms that deal with dynamic links. We introduce a new class of evolving range-dependent random graphs that gives a tractable framework for modelling and simulation. We develop a spectral algorithm for calibrating a set of edge ranges from a sequence of network snapshots and give a proof of principle illustration on some neuroscience data. We also show how the model can be used computationally and analytically to investigate the scenario where an evolutionary process, such as an epidemic, takes place on an evolving network. This allows us to study the cumulative effect of two distinct types of dynamics.

Hierarchical composite regular parallel architecture

The design space of emerging heterogenous multi-core architectures with re-configurability element makes it feasible to design mixed fine-grained and coarse-grained parallel architectures. This paper presents a hierarchical composite array design which extends the curret design space of regular array design by combining a sequence of transformations. This technique is applied to derive a new design of a pipelined parallel regular array with different dataflow between phases of computation.

Efficient FPGA-based regular expression pattern matching

An approach to the automatic generation of efficient Field Programmable Gate Arrays (FPGAs) circuits for the Regular Expression-based (RegEx) Pattern Matching problems is presented. Using a novel design strategy, as proposed, circuits that are highly area-and-time-efficient can be automatically generated for arbitrary sets of regular expressions. This makes the technique suitable for applications that must handle very large sets of patterns at high speed, such as in the network security and intrusion detection application domains. We have combined several existing techniques to optimise our solution for such domains and proposed the way the whole process of dynamic generation of FPGAs for RegEX pattern matching could be automated efficiently.

Compositional technique for synthesising multi-phase regular arrays

We describe a high-level design method to synthesize multi-phase regular arrays. The method is based on deriving component designs using classical regular (or systolic) array synthesis techniques and composing these separately evolved component design into a unified global design. Similarity transformations ar e applied to component designs in the composition stage in order to align data ow between the phases of the computations. Three transformations are considered: rotation, re ection and translation. The technique is aimed at the design of hardware components for high-throughput embedded systems applications and we demonstrate this by deriving a multi-phase regular array for the 2-D DCT algorithm which is widely used in many vide ocommunications applications.