Branch Prediction For Network Processors

Originally designed to favour flexibility over packet processing performance, the future of the programmable network processor is challenged by the need to meet both increasing line rate as well as providing additional processing capabilities. To meet these requirements, trends within networking research has tended to focus on techniques such as offloading computation intensive tasks to dedicated hardware logic or through increased parallelism. While parallelism retains flexibility, challenges such as load-balancing limit its scope. On the other hand, hardware offloading allows complex algorithms to be implemented at high speed but sacrifice flexibility. To this end, the work in this thesis is focused on a more fundamental aspect of a network processor, the data-plane processing engine. Performing both system modelling and analysis of packet processing functions; the goal of this thesis is to identify and extract salient information regarding the performance of multi-processor workloads. Following on from a traditional software based analysis of programme workloads, we develop a method of modelling and analysing hardware accelerators when applied to network processors. Using this quantitative information, this thesis proposes an architecture which allows deeply pipelined micro-architectures to be implemented on the data-plane while reducing the branch penalty associated with these architectures

Field-based branch prediction for packet processing engines

Network processors have exploited many aspects of architecture design, such as employing multi-core, multi-threading and hardware accelerator, to support both the ever-increasing line rates and the higher complexity of network applications. Micro-architectural techniques like superscalar, deep pipeline and speculative execution provide an excellent method of improving performance without limiting either the scalability or flexibility, provided that the branch penalty is well controlled. However, it is difficult for traditional branch predictor to keep increasing the accuracy by using larger tables, due to the fewer variations in branch patterns of packet processing. To improve the prediction efficiency, we propose a flow-based prediction mechanism which caches the branch histories of packets with similar header fields, since they normally undergo the same execution path. For packets that cannot find a matching entry in the history table, a fallback gshare predictor is used to provide branch direction. Simulation results show that the our scheme achieves an average hit rate in excess of 97.5% on a selected set of network applications and real-life packet traces, with a similar chip area to the existing branch prediction architectures used in modern microprocessors

Clinically driven analysis reveals gene-socioeconomic status interaction influencing periodontal disease in the electronic health record-linked Generation Scotland: Scottish Family Health Study (GS: SFHS) cohort.

Introduction Heritability (proportion of trait variation attributable to genetic factors) is not a fixed property. It can vary across different social settings and environments. Exploration of gene-environment interaction has been limited by lack of large sample sizes. Biobanks linked to electronic health records pose a solution to this sample size problem. Objectives and Approach Social inequalities in periodontal health have been well documented in the dental scientific literature. However, gene-socioeconomic status interaction has yet to be examined. We identified 2,192 cases and 11,525 controls from linked electronic periodontal treatment records within the Generation Scotland: Scottish Family Health Study (GS: SFHS) (www.generationscotland.org). The measure of socioeconomic status used was the Scottish Index of Multiple Deprivation. The objective of this study was to investigate the gene-socioeconomic status interaction within this data. A reaction norm model was used to evaluate the presence of a gene-socioeconomic status interaction in the statistical software ASReml. Results We estimated the heritability of periodontal disease at 10.42% (95% confidence interval 5.97-14.88%). Socioeconomic status modified the heritability of periodontal disease. The heritability of was 13.37%, 0.14% and 11.70% in areas of high, moderate and low deprivation respectively; indicating the occurrence of a gene-socioeconomic status interaction with periodontal disease. These results indicate that socioeconomic status explains a large portion of genetic variation in periodontal disease risk. This information suggests that effective intervention and prevention programs for periodontal disease should involve socioeconomic aspects in their planning, implementations and evaluation. For instance, interventions targeted to reduce smoking in more deprived subjects with a genetic predisposition to periodontal disease could enhance the effect of health promotion strategies in reducing risk. Conclusion/Implications This study presents contemporary evidence in a large population based cohort that gene-socioeconomic interaction leads to the progression of periodontal disease. This information may lead to the development of better preventative strategies for clinical dentistry

The Roots of Diversity: Below Ground Species Richness and Rooting Distributions in a Tropical Forest Revealed by DNA Barcodes and Inverse Modeling

F. Andrew Jones is with the Smithsonian Tropical Research Institute, David L. Erickson is with the Smithsonian Institution, Moises A. Bernal is with the Smithsonian Tropical Research Institute and UT Austin, Eldredge Bermingham is with the Smithsonian Tropical Research Institute, W. John Kress is with the Smithsonian Institution, Edward Allen Herre is with the Smithsonian Tropical Research Institute, Helene C. Muller-Landau is with the Smithsonian Tropical Research Institute, Benjamin L. Turner is with the Smithsonian Tropical Research Institute.Background -- Plants interact with each other, nutrients, and microbial communities in soils through extensive root networks. Understanding these below ground interactions has been difficult in natural systems, particularly those with high plant species diversity where morphological identification of fine roots is difficult. We combine DNA-based root identification with a DNA barcode database and above ground stem locations in a floristically diverse lowland tropical wet forest on Barro Colorado Island, Panama, where all trees and lianas >1 cm diameter have been mapped to investigate richness patterns below ground and model rooting distributions. Methodology/Principal Findings -- DNA barcode loci, particularly the cpDNA locus trnH-psba, can be used to identify fine and small coarse roots to species. We recovered 33 species of roots from 117 fragments sequenced from 12 soil cores. Despite limited sampling, we recovered a high proportion of the known species in the focal hectare, representing approximately 14% of the measured woody plant richness. This high value is emphasized by the fact that we would need to sample on average 13 m2 at the seedling layer and 45 m2 for woody plants >1 cm diameter to obtain the same number of species above ground. Results from inverse models parameterized with the locations and sizes of adults and the species identifications of roots and sampling locations indicates a high potential for distal underground interactions among plants. Conclusions -- DNA barcoding techniques coupled with modeling approaches should be broadly applicable to studying root distributions in any mapped vegetation plot. We discuss the implications of our results and outline how second-generation sequencing technology and environmental sampling can be combined to increase our understanding of how root distributions influence the potential for plant interactions in natural ecosystems.FAJ acknowledges the support of a Tupper postdoctoral fellowship in tropical biology and the National Science Foundation (DEB 0453665). Funding was provided by the Smithsonian Institution Global Earth Observatory, the Smithsonian Tropical Research Institute/Center for Tropical Forest Sciences endowment fund, and the Smithsonian Tropical Research Institute/Frank Levinson fund. We would like to thank Autoridad Nacional del Ambiente and the Smithsonian Tropical Research Institute for processing research permits. We thank S. Hubbell and R. Condit for access to plot data, S. Schnitzer for liana census data (NSF DEB 0613666), and L. Comita and S. Hubbell for access to seedling data (NSF DEB 0075102 and DEB 0823728). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Marine Scienc

Stakeholders’ knowledge, attitudes and practices to pharmacovigilance and adverse drug reaction reporting in clinical trials: a mixed methods study

Purpose: The purpose of this study was to explore the knowledge, attitudes and practices of health professionals working in clinical trials, to pharmacovigilance and adverse drug reaction (ADR) reporting. Methods: A mixed methods study comprising an online questionnaire disseminated from September to November 2018, three semi-structured interviews and four focus groups. The qualitative components were conducted with a random sample of questionnaire participants who had provided their contact details (n = 24). The qualitative interviews were conducted at a location convenient to the participant’s place of work between October and December 2018. Results: One hundred forty-eight participants completed the questionnaire. Study coordinators/project managers represented the largest group of participants ( 28.6%, n = 38). Poor knowledge or understanding of ADR reporting was the most frequently cited barrier to ADR reporting (75%, n = 93). The most common enabler to reporting was having a clear understanding of an ADR definition (85.7%, n = 108). Focus group and interview participants described having limited staff as a barrier to reporting an ADR. They welcomed the prospect of pharmacovigilance training and indicated that face-to-face training would be preferred to provision of online training. Conclusion: This study highlights key factors that influence the reporting of ADRs in clinical trials. Although the findings are specifically related to the clinical trial environment in Ireland, they may provide a useful platform for optimising the future conduct of trials. This research suggests that ADR reporting may be improved through provision of enhanced pharmacovigilance training to clinical trial staff

The potential for grain refinement of wire-arc additive manufactured (WAAM) Ti-6Al-4V by ZrN and TiN inoculation

Wire-Arc Additive Manufacturing (WAAM) of large near-net-shape titanium components has the potential to reduce costs and lead-time in many industrial sectors including aerospace. However, with titanium alloys, such as Ti-6Al-4V, standard WAAM processing conditions result in solidification microstructures comprising large cm-scale, fibre textured, columnar β grains, which are detrimental to mechanical performance. In order to reduce the size of the solidified β-grains, as well as refine their columnar morphology and randomise their texture, two cubic nitride phases, TiN and ZrN were investigated as potential grain refining inoculants. To avoid the cost of manufacturing new wire, experimental trials were performed using powder adhered to the surface of the deposited tracks. With TiN particle additions, the β grain size was successfully reduced and modified from columnar to equiaxed grains, with an average size of 300 µm, while ZrN powder was shown to be ineffective at low addition levels studied. Clusters of TiN particles were found to be responsible for nucleating multiple β Ti grains. By utilizing the Burgers orientation relationship, EBSD investigation showed that a Kurdjumov-Sachs orientation relationship could be demonstrated between the refined primary β grains and TiN particles

Birth weight associations with DNA methylation differences in an adult population

The Developmental Origins of Health and Disease (DOHaD) theory predicts that prenatal and early life events shape adult health outcomes. Birth weight is a useful indicator of the foetal experience and has been associated with multiple adult health outcomes. DNA methylation (DNAm) is one plausible mechanism behind the relationship of birth weight to adult health. Through data linkage between Generation Scotland and historic Scottish birth cohorts, and birth records held through the NHS Information and Statistics Division, a sample of 1,757 individuals with available birth weight and DNAm data was derived. Epigenome-wide association studies (EWAS) were performed in two independently generated DNAm subgroups (n(Set1) = 1,395, n(Set2) = 362), relating adult DNAm from whole blood to birth weight. Meta-analysis yielded one genome-wide significant CpG site (p = 5.97x10(−9)), cg00966482. There was minimal evidence for attenuation of the effect sizes for the lead loci upon adjustment for numerous potential confounder variables (body mass index, educational attainment, and socioeconomic status). Associations between birth weight and epigenetic measures of biological age were also assessed. Associations between lower birth weight and higher Grim Age acceleration (p((FDR)) = 3.6x10(−3)) and shorter DNAm-derived telomere length (p((FDR)) = 1.7x10(−3)) are described, although results for three other epigenetic clocks were null. Our results provide support for an association between birth weight and DNAm both locally at one CpG site, and globally via biological ageing estimates

Monitoring the emergence of community transmission of influenza A/H1N1 2009 in England: a cross sectional opportunistic survey of self sampled telephone callers to NHS Direct

Objective To evaluate ascertainment of the onset of community transmission of influenza A/H1N1 2009 (swine flu) in England during the earliest phase of the epidemic through comparing data from two surveillance systems