Accelerating Discrete Wavelet Transforms on GPUs

The two-dimensional discrete wavelet transform has a huge number of applications in image-processing techniques. Until now, several papers compared the performance of such transform on graphics processing units (GPUs). However, all of them only dealt with lifting and convolution computation schemes. In this paper, we show that corresponding horizontal and vertical lifting parts of the lifting scheme can be merged into non-separable lifting units, which halves the number of steps. We also discuss an optimization strategy leading to a reduction in the number of arithmetic operations. The schemes were assessed using the OpenCL and pixel shaders. The proposed non-separable lifting scheme outperforms the existing schemes in many cases, irrespective of its higher complexity.Comment: preprint submitted to ICIP 2017. arXiv admin note: substantial text overlap with arXiv:1704.0865

Wind-Stress Dust Lifting in a Mars Global Circulation Model: Representation across Resolutions

The formation of Martian dust storms is believed to be driven by dust lifting by near-surface wind stress (NSWS). Accurately representing this dust lifting within Mars Global Circulation Models (MGCMs) is important in order to gain a full understanding of the Martian dust storm cycle. Parameterisations of dust lifting by NSWS exist within several MGCMs; implementations differ but they all follow a similar design, so progress within one model is relevant to the entire field. Few studies have explored in detail how the results of these parameterisations can be affected by changing the horizontal resolution of the model. An accurate parameterisation of dust lifting by NSWS will lift a representative dust mass, reproducing characteristic dust optical depths in the atmosphere. The geographical distribution of the dust lifting by NSWS will also change throughout the year, affecting patterns of dust storm formation and development. Currently, suitable values for dust lifting parameters must be identified at every new model resolution. Resolutions of ~5° latitude x ~5° longitude are often used to model the Martian climate, as thermal tides and long-term weather patterns can be well represented at this resolution. However, smaller scale phenomena (such as near-surface winds driven by local topography) cannot be accurately depicted at this resolution. We use the LMD-UK MGCM to complete multi-year simulations across multiple model resolutions. Our experiments range from ‘low’ resolution ~5° lat x ~5° lon to ‘high’ resolution ~1° lat x ~1° lon. In experiments with fixed, constant lifting parameters, we find that higher resolution simulations lift more dust, but that this trend is asymptotic. At low resolutions, dust lifting increases proportionately with the increase in number of horizontal gridboxes. However, at high resolutions, doubling the number of gridboxes results only in a 30% increase in the total dust mass lifted. Geographical and temporal distributions of dust lifting are investigated, as well as the total dust lifted, in order to assess the optimum parameters for each resolution, and to develop a calibration scheme for this dust lifting across model resolutions. The scheme is verified through comparison with spacecraft observations of dust optical depths and dust storm locations

Simple anthropometric and physical performance tests to predict maximal box-lifting ability

Box-lifting ability is an important characteristic of military personnel. The purpose of this paper was to determine the usefulness of the upright row free weight exercise, and simple anthropometric tests, to predict maximal box-lifting performance that simulates the loading of military supply vehicles. Two groups of adults performed maximal box lifts to 1.4 m (study one) and 1.7 m (study two) respectively. All subjects were also tested for upright row 1-repetition maximum (1RM) strength, body mass, height and body composition. In study one, a remarkably good prediction of maximal box-lift performance to 1.4 m (42 ? 12 kg) was obtained from a regression equation including the variables body mass, body composition and upright row 1RM. Approximately 95% of the variation in 1.4 m box-lifting performance could be accounted for. In contrast, in study two, only 80% of the variation in 1.7 m box-lifting performance (51 ? 15 kg) could be accounted for by the best predictor equation. Upright row 1RM strength appears to be a useful tool in the prediction of box-lifting ability to approximately chest height for most adults, probably due to a close match between the muscle groups and contraction modes required during both tasks. Military or other organizations could use the data reported here to substitute simple anthropometry and a 1RM test of strength and for the direct assessment of 1.4 m box-lifting performance