An Application-Oriented Synthetic Network Traffic Generator

Abstract—Design space exploration and detailed anal-ysis in the field of hardware design applies simulation in many variants. A frequently used method is stochastic simulation where systems are stimulated by randomised input. Synthetic traffic traces mainly form the load for stochastic simulation of network computing devices. The generator presented here utilises two well-known models to meet the features of a majority of applications and traffic sources. Based on application-specific pa-rameter sets, the traffic models stochastically generate packet flows which are merged to an aggregated stream. Nevertheless, all packets can always be identified and are not resolved to a data mass representing the load of a link

Germline variation at 8q24 and prostate cancer risk in men of European ancestry

Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10−15), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62–4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Peer reviewe

Multiprocessor Testbed DIRMU 25

Multiprocessor Testbed DIRMU 25 : efficiency and fault tolerance. - In: Parallel systems and computation / ed. by George Paul ... - Amsterdam u. a. : North Holland Publ., 1988. - S. 149-163

Architektur fehlertoleranter Systeme

Architektur fehlertoleranter Systeme. - In: Informationstechnik. 30. 1988. S. 169-179

RTeasy An Algorithmic Design Environment on Register Transfer Level Abstract

Current developer tools and HDLs for system design are powerful instruments and support a variety of abstraction levels but they are too complex for didactic purposes. This paper describes the RTeasy IDE, an algorithmic design environment on register transfer level that has been developed to provide a simple system-design tool for didactic purposes to be used e.g. in introductory courses in computer engineering and digital design. The RTeasy tool suite includes an HDL, a simulator and further design features. As an example, it is applied to the design flow of a shift-multiplier.

Distributed Fault-Tolerant Robot Control Architecture Based on Organic Computing Principles

Abstract Walking animals like insects show a great repertoire of reactions and behaviours in interaction with their environment. Moreover, they are very adaptive to changes in their environment and to changes of their own body like injuries. Even after the loss of sensors like antennas or actuators like legs, insects show an amazing fault tolerance without any hint of great computational power or complex internal fault models. Our most complex robots in contrast lack the insect abilities although computational power is getting better and better. Understanding biological concepts and learning from nature could improve our approaches and help us to make our systems more &quot;life-like&quot; and therefore more fault tolerant. This article introduces a control architectural approach based on organic computing principles using concepts of decentralization and self-organization, which is demonstrated and tested on a six-legged robotic platform. Beside explaining the organic robot control architecture, this study presents a leg coordination architecture extension to improve the robustness and dependability towards structural body modifications like leg amputations and compares experimental results with previous studies

A Design Technique for Adapting Number and Boundaries of Reconfigurable Modules at Runtime

Runtime reconfigurable system-on-chip designs for FPGAs pose manifold demands on the underlying system architecture and design tool capabilities. The system architecture has to support varying communication needs of a changing number of processing units mapped onto diverse locations. Design tools should support an arbitrary placement of processing modules and the adjustment of boundaries of reconfigurable regions to the size of the actually instantiated processing modules. While few works address the design of flexible system architectures, the adjustment of boundaries of reconfigurable regions to the size of the actually instantiated processing modules is hardly ever considered due to design tool limitations. In this paper, a technique for circumventing this restriction is presented. It allows for a rededication of the reconfigurable area to a different number of individually sized reconfigurable regions. This technique is embedded in the design flow of a runtime reconfigurable system architecture for Xilinx Virtex-4 FPGAs. The system architecture will also be presented to provide a realistic application example