Dynamic group communication for large-scale parallel data mining

Exascale systems are the next frontier in high-performance computing and are expected to deliver a performance of the order of 10^18 operations per second using massive multicore processors. Very large- and extreme-scale parallel systems pose critical algorithmic challenges, especially related to concurrency, locality and the need to avoid global communication patterns. This work investigates a novel protocol for dynamic group communication that can be used to remove the global communication requirement and to reduce the communication cost in parallel formulations of iterative data mining algorithms. The protocol is used to provide a communication-efficient parallel formulation of the k-means algorithm for cluster analysis. The approach is based on a collective communication operation for dynamic groups of processes and exploits non-uniform data distributions. Non-uniform data distributions can be either found in real-world distributed applications or induced by means of multidimensional binary search trees. The analysis of the proposed dynamic group communication protocol has shown that it does not introduce significant communication overhead. The parallel clustering algorithm has also been extended to accommodate an approximation error, which allows a further reduction of the communication costs. The effectiveness of the exact and approximate methods has been tested in a parallel computing system with 64 processors and in simulations with 1024 processing elements.

Goal sketching: towards agile requirements engineering

This paper describes a technique that can be used as part of a simple and practical agile method for requirements engineering. The technique can be used together with Agile Programming to develop software in internet time. We illustrate the technique and introduce lazy refinement, responsibility composition and context sketching. Goal sketching has been used in a number of real-world development projects, one of which is described here.

Engineering of a monodisperse core-shell magnetic Ti-O-Si oxidation nanocatalyst

There has been limited development in catalyst carriers for magnetic separations where superparamagnetic nanoparticles of a high saturation magnetization with no coercivity are required to isolate expensive catalyst reagent that are subjected to repeated magnetic cycles. By using simple stepwise layer-by-layer nanochemistry techniques, we show that an fee FePt nanomagnet can be created inside each silica particle with tailored dimensions to great precision. Subsequent engineering of the external surface with Ti-O-Si species in an optimum structure to create a unique interface gives high activity and excellent selectivity of the composite material for the trans-stilbene oxidation to the corresponding epoxide in the presence of tert-butyl hydroperoxide. Thus, a new magnetic separable epoxidation catalyst is described. This work clearly demonstrates the significance of nanoengineering of a single catalyst particle by a bottom-up construction approach in modern catalyst design, which could lead to new catalytic. properties.

Engineering Pt in ceria for a maximum metal-support interaction in catalysis

Conventional supported metal catalysts are metal nanoparticles deposited on high surface area oxide supports with a poorly defined metal−support interface. Typically, the traditionally prepared Pt/ceria catalyzes both methanation (H2/CO to CH4) and water−gas shift (CO/H2O to CO2/H2) reactions. By using simple nanochemistry techniques, we show for the first time that Pt or PtAu metal can be created inside each CeO2 particle with tailored dimensions. The encapsulated metal is shown to interact with the thin CeO2 overlayer in each single particle in an optimum geometry to create a unique interface, giving high activity and excellent selectivity for the water−gas shift reaction, but is totally inert for methanation. Thus, this work clearly demonstrates the significance of nanoengineering of a single catalyst particle by a bottom-up construction approach in modern catalyst design which could enable exploitation of catalyst site differentiation, leading to new catalytic properties.