A Study of Energy and Locality Effects using Space-filling Curves

The cost of energy is becoming an increasingly important driver for the operating cost of HPC systems, adding yet another facet to the challenge of producing efficient code. In this paper, we investigate the energy implications of trading computation for locality using Hilbert and Morton space-filling curves with dense matrix-matrix multiplication. The advantage of these curves is that they exhibit an inherent tiling effect without requiring specific architecture tuning. By accessing the matrices in the order determined by the space-filling curves, we can trade computation for locality. The index computation overhead of the Morton curve is found to be balanced against its locality and energy efficiency, while the overhead of the Hilbert curve outweighs its improvements on our test system.Comment: Proceedings of the 2014 IEEE International Parallel & Distributed Processing Symposium Workshops (IPDPSW

Hybrid Use of OmpSs for a Shock Hydrodynamics Proxy Application

The LULESH proxy application models the behavior of the ALE3D multi-physics code with an explicit shock hydrodynamics problem, and is made in order to evaluate interactions between programming models and architectures, using a representative code significantly less complex than the application it models. As identified in the PRACE deliverable D7.2.1 [1], the OmpSs programming model specifically targets programming at the exascale, and this whitepaper investigates the effectiveness of its support for development on hybrid architectures

Performance Portability of OpenCL with Application to Neural Networks

This whitepaper investigates the parallel performance of a sample application that implements an approximate expectation-maximization method for inferring the network structure and time varying states of a hidden population within the framework of the kinetic Ising model. The size of networks that can yield informative results can be made arbitrarily large, and the long-running computational demand is highly localized, making the application a strong candidate for future exascale platforms. Previous investigations using OpenMP on the Intel Xeon Phi architecture have suggested that the class of accelerator unit may play a significant part in attainable application performance. An OpenCL parallelization enables experiments with a variety of accelerator units. We examine how this programming model affects the performance of a portable implementation, and use it to compare accelerator technologies in terms of their suitability for future extreme-scale computations

Parallel Scalability of Adaptive Mesh Refinement in a Finite Difference Solution to the Shallow Water Equations

The Shallow Water Equations model the fluid dynamics of deep ocean flow, and are used to simulate tides, tsunamis, and storm surges. Numerical solutions using finite difference methods are computationally expensive enough to mandate the use of large computing clusters, and the cost grows not only with the amount of fluid, but also the duration of the simulated event, and the resolution of the approximation. The benefits of increased resolution are mostly connected to regions where complex fluid interactions occur, and are not required globally for the entire simulation. In this paper, we nvestigate the potential for conserving computational resources by applying Adaptive Mesh Refinement to dynamically determined areas of the fluid urface. We implement adaptive mesh refinement in a MacCormack finite difference solver, develop a performance model to predict its behavior on large-scale parallel platforms, and validate its predictions experimentally on two computing clusters. We find that the solver itself has highly favorable parallel scalability, and that the addition of refined areas introduces a performance penalty due to load imbalance that is at most proportional to the refinement degree raised to the third power

Error control for statistical solutions

Statistical solutions have recently been introduced as a an alternative solution framework for hyperbolic systems of conservation laws. In this work we derive a novel a posteriori error estimate in the Wasserstein distance between dissipative statistical solutions and numerical approximations, which rely on so-called regularized empirical measures. The error estimator can be split into deterministic parts which correspond to spatio-temporal approximation errors and a stochastic part which reflects the stochastic error. We provide numerical experiments which examine the scaling properties of the residuals and verify their splitting.Comment: 25 pages, 2 figure

Feasibility of Optimizations Requiring Bounded Treewidth in a Data Flow Centric Intermediate Representation

Data flow analyses are instrumental to effective compiler optimizations, and are typically implemented by extracting implicit data flow information from traversals of a control flow graph intermediate representation. The Regionalized Value State Dependence Graph is an alternative intermediate representation, which represents a program in terms of its data flow dependencies, leaving control flow implicit. Several analyses that enable compiler optimizations reduce to NP-Complete graph problems in general, but admit linear time solutions if the graph’s treewidth is limited. In this paper, we investigate the treewidth of application benchmarks and synthetic programs, in order to identify program features which cause the treewidth of its data flow graph to increase, and assess how they may appear in practical software. We find that increasing numbers of live variables cause unbounded growth in data flow graph treewidth, but this can ordinarily be remedied by modular program design, and monolithic programs that exceed a given bound can be efficiently detected using an approximate treewidth heuristic

Internationalization Strategies in the German Dairy Industry and their Influence on the Economic Performance of Firms

Growing  milk  production,  stagnating  domestic  consumption  and  ongoing  liberalization  of  the  worldwide  milk  market  have  led  to  increasing  exports  of  milk  and  milk  products  out  of  Germany.  This  situation  heightens competition amongst German dairies for market share on foreign markets. The German dairy industry, which  comprises of some international corporations and many medium sized companies, including both cooperatives and  privately owned companies, therefore has to find strategies with which to compete successfully on international  markets. This study analyzes the German dairy industry comparing different internationalization strategies and their  influence on the firms’ economic success. 18 German dairy companies have been analyzed. We identified different  internationalization strategies with reference to Perlmutter’s EPRG model. To measure economic success, we  analyzed annual reports from the dairy companies observed over the years 2010 to 2017 and so calculated different  key figures. The influence of different internationalization strategies on economic success is analyzed by a Hausman  Taylor estimation where the EBIT‐margin is the dependent variable in our model, representing economic success.  We found that German dairy industry companies do pursue different internationalisation strategies and that these  have different influences on the companies’ economic success

Internationalization Strategies in the German Dairy Industry and their Influence on the Economic Performance of Firms

Growing  milk  production,  stagnating  domestic  consumption  and  ongoing  liberalization  of  the  worldwide  milk  market  have  led  to  increasing  exports  of  milk  and  milk  products  out  of  Germany.  This  situation  heightens competition amongst German dairies for market share on foreign markets. The German dairy industry, which  comprises of some international corporations and many medium sized companies, including both cooperatives and  privately owned companies, therefore has to find strategies with which to compete successfully on international  markets. This study analyzes the German dairy industry comparing different internationalization strategies and their  influence on the firms’ economic success. 18 German dairy companies have been analyzed. We identified different  internationalization strategies with reference to Perlmutter’s EPRG model. To measure economic success, we  analyzed annual reports from the dairy companies observed over the years 2010 to 2017 and so calculated different  key figures. The influence of different internationalization strategies on economic success is analyzed by a Hausman  Taylor estimation where the EBIT‐margin is the dependent variable in our model, representing economic success.  We found that German dairy industry companies do pursue different internationalisation strategies and that these  have different influences on the companies’ economic success