Enhanced Data Parallelism for Irregular Memory Access Optimization on GPU

The use of many-core architectures improves the performance of most of the data-intensive applications. One of the challenging tasks for modern many-core architectures is to handle the irregular memory access effectively. Unlike regular memory access applications, an increase in the size of the problem in an irregular memory access application leads to a reduction in overall performance. A mapping between on-chip and off-chip memory through the heterogeneous communication channel also poses significant challenges. In this paper, a k-exchange algorithm with ant colony optimization is proposed to improve the performance of irregular memory access applications such as Multi-dimensional Knapsack Problem (MKP) and Traveling Salesman Problem (TSP) on the Graphics Processing Units (GPU). A different set of instances of OR library and TSPLIB are considered for experiments. The obtained results show an improvement in terms of optimal solution and speedup for the MKP and TSP instances

Explainable AI for Soil Fertility Prediction

Soil fertility refers to the ability of soil in a particular area to provide favorable chemical, physical and biological characteristics that help the plant in its growth. It is affected by multiple parameters, from the available concentration of Nitrogen in the soil to the concentration of Organic Carbon in the soil. This paper discusses the implementation of an explainable AI (XAI) model based on a Random Forest classifier. The developed model reliably predicts the relative soil fertility of a given soil using its various physiochemical properties, and explain the reasons behind the model’s soil fertility indicator prediction using user friendly graphs. The model shows 97.02% accuracy in comparison with state-of-the-art machine learning models. The paper also discusses applications of developed model in providing possible solutions to further improve upon soil fertility in the short term and long term

Origin of high fluoride in groundwater of the Tuticorin district, Tamil Nadu, India

Abstract This paper reports the results of higher F− and $${\text{HCO}}_{3}^{ - }$$ HCO3- concentrations and its response to high pH level in a hard rock terrain in Tamil Nadu, India. About 400 groundwater samples from the study area were collected from a period of four different seasons and analysed for F−, $${\text{HCO}}_{3}^{ - }$$ HCO3- and other major cations and anions. The key rationale for the higher fluoride and bicarbonate in the study area is the soaring rate of the leaching fluoride-bearing minerals and weathering processes. Fluoride and $${\text{HCO}}_{3}^{ - }$$ HCO3- ranges from BDL to 3.30 mgl−1 and 12 to 940 mgl−1, its concentrations are lower for the period of SWM and it increases during POM and reaches to a maximum in PRM. Higher dissolution is observed in the NEM season due to rainfall impact. Spatial distribution and factor score show that the higher concentrations of F− and $${\text{HCO}}_{3}^{ - }$$ HCO3- are eminent in the northern and central zone of the study area due to the impact of lithology. The higher values in pCO2 versus $${\text{HCO}}_{3}^{ - }$$ HCO3- plot indicate higher residence time which favours more water–rock interactions, which further increase the F− concentrations in groundwater. $${\text{HCO}}_{3}^{ - }$$ HCO3- is linearly correlated with F− which indicates that these ions were consequent from the weathering influences. At the same time, poor correlation of F− with pH could possibly be due to the increase of alkalinity follow-on from the swell of bicarbonate level with very low Ca2+ that promotes increase in F−concentration in the groundwater