Adaptive runtime-assisted block prefetching on chip-multiprocessors

Memory stalls are a significant source of performance degradation in modern processors. Data prefetching is a widely adopted and well studied technique used to alleviate this problem. Prefetching can be performed by the hardware, or be initiated and controlled by software. Among software controlled prefetching we find a wide variety of schemes, including runtime-directed prefetching and more specifically runtime-directed block prefetching. This paper proposes a hybrid prefetching mechanism that integrates a software driven block prefetcher with existing hardware prefetching techniques. Our runtime-assisted software prefetcher brings large blocks of data on-chip with the support of a low cost hardware engine, and synergizes with existing hardware prefetchers that manage locality at a finer granularity. The runtime system that drives the prefetch engine dynamically selects which cache to prefetch to. Our evaluation on a set of scientific benchmarks obtains a maximum speed up of 32 and 10 % on average compared to a baseline with hardware prefetching only. As a result, we also achieve a reduction of up to 18 and 3 % on average in energy-to-solution.Peer ReviewedPostprint (author's final draft

Improving rainfall nowcasting and urban runoff forecasting through dynamic radar-raingauge rainfall adjustment

The insufficient accuracy of radar rainfall estimates is a major source of uncertainty in short-term quantitative precipitation forecasts (QPFs) and associated urban flood forecasts. This study looks at the possibility of improving QPFs and urban runoff forecasts through the dynamic adjustment of radar rainfall estimates based on raingauge measurements. Two commonly used techniques (Kriging with External Drift (KED) and mean field bias correction) were used to adjust radar rainfall estimates for a large area of the UK (250,000 km2) based on raingauge data. QPFs were produced using original radar and adjusted rainfall estimates as input to a nowcasting algorithm. Runoff forecasts were generated by feeding the different QPFs into the storm water drainage model of an urban catchment in London. The performance of the adjusted precipitation estimates and the associated forecasts was tested using local rainfall and flow records. The results show that adjustments done at too large scales cannot provide tangible improvements in rainfall estimates and associated QPFs and runoff forecasts at small scales, such as those of urban catchments. Moreover, the results suggest that the KED adjusted rainfall estimates may be unsuitable for generating QPFs, as this method damages the continuity of spatial structures between consecutive rainfall fields

Climate Change Adaptations for Food Security in Vulnerable Areas of the Egyptian Nile - For Tackling the Overlooked Nexus Hazards of Hydrological Extremes and Waste Pollutions

This is the final version. Available on open access from MDPI via the DOI in this record. Data Availability Statement: No new data were created or analysed in this study. Data sharing is not applicable to this article.The Nile Delta has been suffering from complex environmental hazards caused by climate change and human-induced evolvements, which have led to adverse impacts on national food security. An unfavourable nexus between solid waste management issues and extreme hydrological events is examined mainly through extensive field investigation and literature research, which is an emerging issue affecting food safety and security whilst still being overlooked so far. The findings not only reveal the significance of the emerging issue but also support our proposed recommendations in the policy/legislation and technology sphere. This interdisciplinary research employs a holistic lens that covers diverse perspectives, including systemic problems, wastewater treatment, and environmental neuroscience, to explore the relationship between food, climate change, water management, and waste pollution, and to achieve novel discoveries for the practical adaptations of Egypt’s challenges.Newton-Mosharafa FundUK Department of Business, Energy and Industrial Strategy (BEIS)Egypt Science and Technology Development Fund (STDF

Considering rain gauge uncertainty using Kriging for Uncertain Data

In urban hydrological models, rainfall is the main input and one of the main sources of uncertainty. To reach sufficient spatial coverage and resolution, the integration of several rainfall data sources, including rain gauges and weather radars, is often necessary. The uncertainty associated with rain gauge measurements is dependent on rainfall intensity and on the characteristics of the devices. Common spatial interpolation methods do not account for rain gauge uncertainty variability. Kriging for Uncertain Data (KUD) allows the handling of the uncertainty of each rain gauge independently, modelling space- and time-variant errors. The applications of KUD to rain gauge interpolation and radar-gauge rainfall merging are studied and compared. First, the methodology is studied with synthetic experiments, to evaluate its performance varying rain gauge density, accuracy and rainfall field characteristics. Subsequently, the method is applied to a case study in the Dommel catchment, the Netherlands, where high-quality automatic gauges are complemented by lower-quality tipping-bucket gauges and radar composites. The case study and the synthetic experiments show that considering measurement uncertainty in rain gauge interpolation usually improves rainfall estimations, given a sufficient rain gauge density. Considering measurement uncertainty in radar-gauge merging consistently improved the estimates in the tested cases, thanks to the additional spatial information of radar rainfall data but should still be used cautiously for convective events and low-density rain gauge networks.</p

Comparing Approaches to Deal with Non-Gaussianity of Rainfall Data in Kriging-Based Radar-Gauge Rainfall Merging

Merging radar and rain gauge rainfall data is a technique used to improve the quality of spatial rainfall estimates and in particular the use of Kriging with External Drift (KED) is a very effective radar-rain gauge rainfall merging technique. However, kriging interpolations assume Gaussianity of the process. Rainfall has a strongly skewed, positive, probability distribution, characterized by a discontinuity due to intermittency. In KED rainfall residuals are used, implicitly calculated as the difference between rain gauge data and a linear function of the radar estimates. Rainfall residuals are non-Gaussian as well. The aim of this work is to evaluate the impact of applying KED to non-Gaussian rainfall residuals, and to assess the best techniques to improve Gaussianity. We compare Box-Cox transformations with λ parameters equal to 0.5, 0.25, and 0.1, Box-Cox with time-variant optimization of λ, normal score transformation, and a singularity analysis technique. The results suggest that Box-Cox with λ = 0.1 and the singularity analysis is not suitable for KED. Normal score transformation and Box-Cox with optimized λ, or λ = 0.25 produce satisfactory results in terms of Gaussianity of the residuals, probability distribution of the merged rainfall products, and rainfall estimate quality, when validated through cross-validation. However, it is observed that Box-Cox transformations are strongly dependent on the temporal and spatial variability of rainfall and on the units used for the rainfall intensity. Overall, applying transformations results in a quantitative improvement of the rainfall estimates only if the correct transformations for the specific data set are used.ISSN:0043-1397ISSN:1944-797

Prosthetic shoulder joint infection by Cutibacterium acnes: does rifampin improve prognosis? a retrospective, multicenter, observational study.

This retrospective, multicenter observational study aimed to describe the outcomes of surgical and medical treatment of C. acnes-related prosthetic joint infection (PJI) and the potential benefit of rifampin-based therapies. Patients with C. acnes-related PJI who were diagnosed and treated between January 2003 and December 2016 were included. We analyzed 44 patients with C. acnes-related PJI (median age, 67.5 years (IQR, 57.3-75.8)); 75% were men. The majority (61.4%) had late chronic infection according to the Tsukayama classification. All patients received surgical treatment, and most antibiotic regimens (43.2%) included β-lactam. Thirty-four patients (87.17%) were cured; five showed relapse. The final outcome (cure vs. relapse) showed a nonsignificant trend toward higher failure frequency among patients with previous prosthesis (OR: 6.89; 95% CI: 0.80-58.90) or prior surgery and infection (OR: 10.67; 95% IC: 1.08-105.28) in the same joint. Patients treated with clindamycin alone had a higher recurrence rate (40.0% vs. 8.8%). Rifampin treatment did not decrease recurrence in patients treated with β-lactams. Prior prosthesis, surgery, or infection in the same joint might be related to recurrence, and rifampin-based combinations do not seem to improve prognosis. Debridement and implant retention appear a safe option for surgical treatment of early PJI