Performance Models for Data Transfers: A Case Study with Molecular Chemistry Kernels

With increasing complexity of hardwares, systems with different memory nodes are ubiquitous in High Performance Computing (HPC). It is paramount to develop strategies to overlap the data transfers between memory nodes with computations in order to exploit the full potential of these systems. In this article, we consider the problem of deciding the order of data transfers between two memory nodes for a set of independent tasks with the objective to minimize the makespan. We prove that with limited memory capacity, obtaining the optimal order of data transfers is a NP-complete problem. We propose several heuristics for this problem and provide details about their favorable situations. We present an analysis of our heuristics on traces, obtained by running 2 molecular chemistry kernels, namely, Hartree-Fock (HF) and Coupled Cluster Single Double (CCSD) on 10 nodes of an HPC system. Our results show that some of our heuristics achieve significant overlap for moderate memory capacities and are very close to the lower bound of makespan

The Underlying Factors of Regional U.S. Hotel Market Resiliency Post 9/11

I was interested in researching the underlying factors that drove resiliency in regional U.S. hotel markets. I did this by conducting an empirical analysis of twenty nine different markets post September 11 and investigating general, leisure and business variables. I concluded that leisure variables were the underlying drivers of resiliency in regional U.S. hotel markets. I then conducted an event study to try to apply my findings to stock market prices of publicly traded hotel companies. Although it was a challenge to differentiate between companies that depended more on leisure versus business customers due to their asset diversification, I categorized each company into one of the two subsets. If my findings held, I would assume that that the cumulative abnormal returns for the companies that relied on business customers would be more negative than the companies who relied on leisure customers. However, this was not the case, so the findings that leisure variables drive market resiliency were not a good predictor of stock market reaction

Networks as ‘laboratories of experience’: exploring the life cycle of the suffrage movement and its aftermath in Ireland 1870–1937

Applying an innovative conceptual framework this article presents an interdisciplinary re-appraisal of the suffrage movement and its aftermath in Ireland throughout the years 1870–1937. New social movement theory is utilised to consider how, in the words of the Italian sociologist Alberto Melucci ‘the submerged networks of social movements are laboratories of experience’. Going beyond the previously published work of each author, this article uses the sociological lens of ‘laboratories of experience’ to re-analyse aspects of the suffrage movement, female activism and the wider women's movement in Ireland. This application of social movement theory to female networks, their origins, aims and strategies, along with their interconnectedness, provides a more nuanced and detailed understanding of the ‘life-cycle’ of this movement. The article aims to demonstrate how an analysis of network dynamics and application of the concept of ‘latency’ is useful in further understanding the significance, impact and longevity of the women's movement in Ireland

Rapid screening of proteolytic enzymes and their inhibitors using fluorescence methods

New fluorescence methods for the determination of proteolytic enzymes and their inhibitors have been investigated. Fluorescence polarisation and energy transfer methods have both been examined and of these two approaches energy transfer methods have proven superior. Out of the energy transfer methods, the use of an over-labelled substrate, which is virtually non-fluorescent but becomes highly fluorescent upon proteolytic liberation of dye-labelled peptides, has been demonstrated to be most successful. A substrate utilising α-casein labelled with a long-wavelength BODIPY® dye has been synthesised and shown to be a suitable intramolecularly quenched conjugate for the determination of proteolytic enzymes and their inhibitors in flow-based screening programmes. [Continues.

The SoLid anti-neutrino detector's readout system

The SoLid collaboration have developed an intelligent readout system to reduce their 3200 silicon photomultiplier detector's data rate by a factor of 10000 whilst maintaining high efficiency for storing data from anti-neutrino interactions. The system employs an FPGA-level waveform characterisation to trigger on neutron signals. Following a trigger, data from a space time region of interest around the neutron will be read out using the IPbus protocol. In these proceedings the design of the readout system is explained and results showing the performance of a prototype version of the system are presented

Bayesian computation via empirical likelihood

Approximate Bayesian computation (ABC) has become an essential tool for the analysis of complex stochastic models when the likelihood function is numerically unavailable. However, the well-established statistical method of empirical likelihood provides another route to such settings that bypasses simulations from the model and the choices of the ABC parameters (summary statistics, distance, tolerance), while being convergent in the number of observations. Furthermore, bypassing model simulations may lead to significant time savings in complex models, for instance those found in population genetics. The BCel algorithm we develop in this paper also provides an evaluation of its own performance through an associated effective sample size. The method is illustrated using several examples, including estimation of standard distributions, time series, and population genetics models.Comment: 21 pages, 12 figures, revised version of the previous version with a new titl

2BAD: an application to estimate the parental contributions during two independent admixture events

Several approaches have been developed to calculate the relative contributions of parental populations in single admixture event scenarios, including Bayesian methods. In many breeds and populations, it may be more realistic to consider multiple admixture events. However, no approach has been developed to date to estimate admixture in such cases. This report describes a program application, 2BAD (for 2-event Bayesian ADmixture), which allows the consideration of up to two independent admixture events involving two or three parental populations and a single admixed population, depending on the number of populations sampled. For each of these models, it is possible to estimate several parameters (admixture, effective sizes, etc.) using an approximate Bayesian computation approach. In addition, the program allows comparing pairs of admixture models, determining which is the most likely given data. The application was tested through simulations and was found to provide good estimates for the contribution of the populations at the two admixture events. We were also able to determine whether an admixture model was more likely than a simple split model