Water quality strategy for the Lockwoods Folly River: A partnership for an ailing river

As with a majority of the remaining undeveloped coastal areas in North Carolina, Brunswick County is not a hidden treasure any more. Since 1980 the county’s population has more than tripled to over 95,000 and another 30,000 or so residents are expected to make this last bastion of undeveloped southeastern NC their home by 2020, even with the current economic downturn. As the 29th fastest growing county in the nation this population explosion is resulting in rapid landscape scale land use changes within the watershed of the Lockwoods Folly River. Subdivisions, shopping centers, new highways and bridges, golf courses, and marinas are becoming significant land use activities. The surging development within this 150-square mile 88 thousand-acre watershed has had a severe effect on the health of the river. The portion of the river closed to shell fishing has more that tripled from 18 percent in 1980 to more than 55 percent today and 60% of the beds are considered impaired. For generations, locals have enjoyed the bounty of the Lockwoods Folly River and estuarine system famed for its rich and abundant shell fish beds and excellent coastal inshore fishing. This river system stretches from the Lockwoods Folly Inlet at the Atlantic Ocean inland where it makes the transformation from saltwater marshes to a winding blackwater river that snakes into hundreds of smaller tributaries and blackwater swamps. (PDF contains 4 pages

Multilevel Monte Carlo methods for applications in finance

Since Giles introduced the multilevel Monte Carlo path simulation method [18], there has been rapid development of the technique for a variety of applications in computational finance. This paper surveys the progress so far, highlights the key features in achieving a high rate of multilevel variance convergence, and suggests directions for future research.Comment: arXiv admin note: text overlap with arXiv:1202.6283; and with arXiv:1106.4730 by other author

The UK workforce : realising our potential

for Business, a new UK-wide network of employer-led Sector Skills Councils (SSCs), supported and directed by the Sector Skills Development Agency (SSDA). The purpose of Skills for Business is to bring employers more centre stage in articulating their skill needs and delivering skills-based productivity improvements that can enhance UK competitiveness and the effectiveness of public services. The remit of the SSDA includes establishing and progressing the network of SSCs, supporting the SSCs in the development of their own capacity and providing a range of core services. Additionally the SSDA has responsibility for representing sectors not covered by a SSC and co-ordinating action on cross cutting and generic skills issues. Research, and developing a sound evidence base, are central to the SSDA and to Skills for Business as a whole. It is crucial in: analysing productivity and skill needs; identifying priorities for action; and improving the evolving policy and skills agenda. It is vital that the SSDA research team works closely with partners already involved in skills and related research to generally drive up the quality o

Improved Acceleration of the GPU Fourier Domain Acceleration Search Algorithm

We present an improvement of our implementation of the Correlation Technique for the Fourier Domain Acceleration Search (FDAS) algorithm on Graphics Processor Units (GPUs) (Dimoudi & Armour 2015; Dimoudi et al. 2017). Our new improved convolution code which uses our custom GPU FFT code is between 2.5 and 3.9 times faster the than our cuFFT-based implementation (on an NVIDIA P100) and allows for a wider range of filter sizes then our previous version. By using this new version of our convolution code in FDAS we have achieved 44% performance increase over our previous best implementation. It is also approximately 8 times faster than the existing PRESTO GPU implementation of FDAS (Luo 2013). This work is part of the AstroAccelerate project (Armour et al. 2002), a many-core accelerated time-domain signal processing library for radio astronomy.Comment: proceeding from ADASS XXVII conference, 4 page

Importance Sampling for Pathwise Sensitivity of Stochastic Chaotic Systems

This paper proposes a new pathwise sensitivity estimator for chaotic SDEs. By introducing a spring term between the original and perturbated SDEs, we derive a new estimator by importance sampling. The variance of the new estimator increases only linearly in time $T,$ compared with the exponential increase of the standard pathwise estimator. We compare our estimator with the Malliavin estimator and extend both of them to the Multilevel Monte Carlo method, which further improves the computational efficiency. Finally, we also consider using this estimator for the SDE with small volatility to approximate the sensitivities of the invariant measure of chaotic ODEs. Furthermore, Richardson-Romberg extrapolation on the volatility parameter gives a more accurate and efficient estimator. Numerical experiments support our analysis.Comment: 29 pages, 31 figure

GPU Fast Convolution via the Overlap-and-Save Method in Shared Memory

We present an implementation of the overlap-and-save method, a method for the convolution of very long signals with short response functions, which is tailored to GPUs. We have implemented several FFT algorithms (using the CUDA programming language), which exploit GPU shared memory, allowing for GPU accelerated convolution. We compare our implementation with an implementation of the overlap-and-save algorithm utilizing the NVIDIA FFT library (cuFFT). We demonstrate that by using a shared-memory-based FFT, we can achieved significant speed-ups for certain problem sizes and lower the memory requirements of the overlap-and-save method on GPUs