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Ptychography is a popular microscopic imaging modality for many scientific discoveries and sets the record for highest image resolution. Unfortunately, the high image resolution for ptychographic reconstruction requires significant amount of memory and computations, forcing many applications to compromise their image resolution in exchange for a smaller memory footprint and a shorter reconstruction time. In this paper, we propose a novel image gradient decomposition method that significantly reduces the memory footprint for ptychographic reconstruction by tessellating image gradients and diffraction measurements into tiles. In addition, we propose a parallel image gradient decomposition method that enables asynchronous point-to-point communications and parallel pipelining with minimal overhead on a large number of GPUs. Our experiments on a Titanate material dataset (PbTiO3) with 16632 probe locations show that our Gradient Decomposition algorithm reduces memory footprint by 51 times. In addition, it achieves time-to-solution within 2.2 minutes by scaling to 4158 GPUs with a super-linear strong scaling efficiency at 364% compared to runtimes at 6 GPUs. This performance is 2.7 times more memory efficient, 9 times more scalable and 86 times faster than the state-of-the-art algorithm.

The chassis of a Formula 1 car is constructed for the most part from carbon fibre reinforced composite materials. Primary structures such as the monocoque/survival cell, suspension and gearboxes and the overwhelming majority of secondary (wings, bodywork, etc.) structures are routinely produced using such materials. During the operation of the vehicles it is fairly commonplace for composite components to sustain a degree of damage. The level of damage varies from being very minor (small holes and dents from stone strikes, etc.) to very serious structural damage to major components resulting from accidents. Although F1 Teams operate with large budgets, the funding available is finite and the logistics very tight such that there is a need, wherever possible, to repair and return to service damaged parts rather than scrap and replace them. This must of course be done in such a way that the safety and performance of the cars are in no way compromised. The repair of composite structures is far from a trivial exercise; the degree of damage must be assessed and a repair scheme “designed” and implemented in the shortest possible time. The degree of invasive “surgery” is kept to the minimum and all corrective work carried out must be fully documented and capable of future condition monitoring as part of the team’s total quality management (TQM) process. Additionally, repair techniques may be used to reverse progressive damage (analogous to metal fatigue) within composite structures thus preventing major failures and extending their service lives. Commonly used repair techniques and methodologies are discussed and illustrated with practical examples culminating with the repair of major structural damage to the monocoque.

A new technique for eliminating Doppler aliasing artifacts in synthetic aperture radar (SAR) imagery is presented. The technique uses continuous transmission of stepped-frequency (SF) waveforms to generate a simple, but effective, approximation of a two-dimensional |sinc|2 ambiguity function. This approach ensures aliasing artifacts are placed at nulls in a Doppler filter, effectively removing them from the imagery. Various methods of generating SF waveforms are introduced and their performance is quantified. Finally, simulated SAR imagery shows elimination of more than 99% of the aliased energy