An efficient sparse conjugate gradient solver using a Beneš permutation network

© 2014 Technical University of Munich (TUM).The conjugate gradient (CG) is one of the most widely used iterative methods for solving systems of linear equations. However, parallelizing CG for large sparse systems is difficult due to the inherent irregularity in memory access pattern. We propose a novel processor architecture for the sparse conjugate gradient method. The architecture consists of multiple processing elements and memory banks, and is able to compute efficiently both sparse matrix-vector multiplication, and other dense vector operations. A Beneš permutation network with an optimised control scheme is introduced to reduce memory bank conflicts without expensive logic. We describe a heuristics for offline scheduling, the effect of which is captured in a parametric model for estimating the performance of designs generated from our approach

On the estimation of the domain of attraction for discrete-time switched and hybrid nonlinear systems

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Protective efficacy of poultry vaccines against recently circulating Highly Pathogenic Avian Influenza (HPAI) H5N1 virus isolater from markets and farms in Hong Kong 2008

Parallel Session 2 - Emerging/Infectious Diseases: no. S7Theme: Translating Health Research into Policy and Practice for Health of the PopulationINTRODUCTION: Highly pathogenic avian influenza (HPAI) H5N1 remains a major threat to animal and public health. Since 2003, Hong Kong has successfully used poultry vaccination as part of its strategy to minimise this threat within Hong Kong. In mid-2008, an HPAI H5N1 outbreak occurred in a vaccinated poultry farm in Hong Kong. AIMS: a) to compare protective efficacy of different poultry vaccines against the 2008 farm outbreak strain; and b) to assess whether there needs to be a change in the poultry vaccine used in Hong Kong. METHODS: White leghorn chickens were raised in a clean laboratory environment and …published_or_final_versio

A domain specific approach to high performance heterogeneous computing

Users of heterogeneous computing systems face two problems: first, in understanding the trade-off relationships between the observable characteristics of their applications, such as latency and quality of the result, and second, how to exploit knowledge of these characteristics to allocate work to distributed computing platforms efficiently. A domain specific approach addresses both of these problems. By considering a subset of operations or functions, models of the observable characteristics or domain metrics may be formulated in advance, and populated at run-time for task instances. These metric models can then be used to express the allocation of work as a constrained integer program. These claims are illustrated using the domain of derivatives pricing in computational finance, with the domain metrics of workload latency and pricing accuracy. For a large, varied workload of 128 Black-Scholes and Heston model-based option pricing tasks, running upon a diverse array of 16 Multicore CPUs, GPUs and FPGAs platforms, predictions made by models of both the makespan and accuracy are generally within 10 percent of the run-time performance. When these models are used as inputs to machine learning and MILP-based workload allocation approaches, a latency improvement of up to 24 and 270 times over the heuristic approach is seen

Homogeneous Polynomial Lyapunov Functions for Robust Local Synchronisation with Time-varying Uncertainties

This study studies robust local synchronisation in multi-agent systems with time-varying parametric uncertainties constrained in a polytope. In contrast to the existing methods with non-convex conditions via using quadratic Lyapunov function, a new criteria is proposed based on using homogeneous polynomial Lyapunov functions where the original system is suitably approximated by an uncertain polytopic system. Furthermore, the corresponding tractable conditions of linear matrix inequalities have been provided by exploiting the squares matrix representation. Then, the polytopic synchronisation margin problem is, for the first time, proposed and investigated via handling generalised eigenvalue problems. Lastly, numerical examples illustrate the usefulness of the proposed method.postprin

Neurorestoratology evidence in an animal model with cervical spondylotic myelopathy

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Wat ben ik toch een groene jongen (m/v)!

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