Mira: A Framework for Static Performance Analysis

The performance model of an application can pro- vide understanding about its runtime behavior on particular hardware. Such information can be analyzed by developers for performance tuning. However, model building and analyzing is frequently ignored during software development until perfor- mance problems arise because they require significant expertise and can involve many time-consuming application runs. In this paper, we propose a fast, accurate, flexible and user-friendly tool, Mira, for generating performance models by applying static program analysis, targeting scientific applications running on supercomputers. We parse both the source code and binary to estimate performance attributes with better accuracy than considering just source or just binary code. Because our analysis is static, the target program does not need to be executed on the target architecture, which enables users to perform analysis on available machines instead of conducting expensive exper- iments on potentially expensive resources. Moreover, statically generated models enable performance prediction on non-existent or unavailable architectures. In addition to flexibility, because model generation time is significantly reduced compared to dynamic analysis approaches, our method is suitable for rapid application performance analysis and improvement. We present several scientific application validation results to demonstrate the current capabilities of our approach on small benchmarks and a mini application

EU Accession Effects on Export Performance: The Case of Greece

This paper estimates the effects on the Greek export performance that caused by the EU accession. A simultaneous equations model of export demand and export supply has been used in order to avoid the simultaneity problem. Comparative static analysis and the residuals approach have been implemented. The results indicate that the EU accession and the consequent abolition of the export subsidies had a negative effect on the country’s export performance, instead of improving it. The main reason for this effect is that the export subsidies, during the time period that were valid, were just improved the exporters’ revenues and not used for creating new comparative advantages for the Greek products.EU Accession, Export subsidies, Simultaneous equations, Comparative static

pandapower - an Open Source Python Tool for Convenient Modeling, Analysis and Optimization of Electric Power Systems

pandapower is a Python based, BSD-licensed power system analysis tool aimed at automation of static and quasi-static analysis and optimization of balanced power systems. It provides power flow, optimal power flow, state estimation, topological graph searches and short circuit calculations according to IEC 60909. pandapower includes a Newton-Raphson power flow solver formerly based on PYPOWER, which has been accelerated with just-in-time compilation. Additional enhancements to the solver include the capability to model constant current loads, grids with multiple reference nodes and a connectivity check. The pandapower network model is based on electric elements, such as lines, two and three-winding transformers or ideal switches. All elements can be defined with nameplate parameters and are internally processed with equivalent circuit models, which have been validated against industry standard software tools. The tabular data structure used to define networks is based on the Python library pandas, which allows comfortable handling of input and output parameters. The implementation in Python makes pandapower easy to use and allows comfortable extension with third-party libraries. pandapower has been successfully applied in several grid studies as well as for educational purposes. A comprehensive, publicly available case-study demonstrates a possible application of pandapower in an automated time series calculation

An extreme critical space-time: echoing and black-hole perturbations

A homothetic, static, spherically symmetric solution to the massless Einstein- Klein-Gordon equations is described. There is a curvature singularity which is central, null, bifurcate and marginally trapped. The space-time is therefore extreme in the sense of lying at the threshold between black holes and naked singularities, just avoiding both. A linear perturbation analysis reveals two types of dominant mode. One breaks the continuous self-similarity by periodic terms reminiscent of discrete self-similarity, with echoing period within a few percent of the value observed numerically in near-critical gravitational collapse. The other dominant mode explicitly produces a black hole, white hole, eternally naked singularity or regular dispersal, the latter indicating that the background is critical. The black hole is not static but has constant area, the corresponding mass being linear in the perturbation amplitudes, explicitly determining a unit critical exponent. It is argued that a central null singularity may be a feature of critical gravitational collapse.Comment: 6 revtex pages, 6 eps figure

Dynamic resiliency analysis of key predistribution in wireless sensor networks

Wireless sensor networks have been analyzed for more than a decade from operational and security points of view. Several key predistribution schemes have been proposed in the literature. Although valuable and state-of-the-art proposals have been made, their corresponding security analyses have not been performed by considering the dynamic nature of networking behavior and the time dimension. The sole metric used for resiliency analysis of key predistribution schemes is "fraction of links compromised" which is roughly defined as the ratio of secure communication links that the adversary can compromise over all secure links. However, this metric does not consider the dynamic nature of the network; it just analyzes a snapshot of the network without considering the time dimension. For example, possible dead nodes may cause change of routes and some captured links become useless for the attacker as time goes by. Moreover, an attacker cannot perform sensor node capturing at once, but performs over time. That is why a methodology for dynamic security analysis is needed in order to analyze the change of resiliency in time a more realistic way. In this paper, we propose such a dynamic approach to measure the resiliency of key predistribution schemes in sensor networks. We take the time dimension into account with a new performance metric, "captured message fraction". This metric is defined as the percentage of the messages generated within the network to be forwarded to the base station (sink) that are captured and read by the attacker. Our results show that for the cases where the static fraction of links compromised metric indicates approximately 40% of the links are compromised, our proposed captured message fraction metric shows 80% of the messages are captured by the attacker. This clearly proves the limitations of the static resiliency analysis in the literature

Event-based contact angle measurements inside porous media using time-resolved micro-computed tomography

Hypothesis: Capillary-dominated multiphase flow in porous materials is strongly affected by the pore walls' wettability. Recent micro-computed tomography (mCT) studies found unexpectedly wide contact angle distributions measured on static fluid distributions inside the pores. We hypothesize that analysis on time-resolved mCT data of fluid invasion events may be more directly relevant to the fluid dynamics. Experiment: We approximated receding contact angles locally in time and space on time-resolved mCT datasets of drainage in a glass bead pack and a limestone. Whenever a meniscus suddenly entered one or more pores, geometric and thermodynamically consistent contact angles in the surrounding pores were measured in the time step just prior to the displacement event. We introduced a new force-based contact angle, defined to recover the measured capillary pressure in the invaded pore throat prior to interface movement. Findings: Unlike the classical method, the new geometric and force-based contact angles followed plausible, narrower distributions and were mutually consistent. We were unable to obtain credible results with the thermodynamically consistent method, likely because of sensitivity to common imaging artifacts and neglecting dissipation. Time-resolved mCT analysis can yield a more appropriate wettability characterization for pore scale models, despite the need to further reduce image analysis uncertainties. (C) 2020 The Authors. Published by Elsevier Inc

Advanced optical imaging in living embryos

Developmental biology investigations have evolved from static studies of embryo anatomy and into dynamic studies of the genetic and cellular mechanisms responsible for shaping the embryo anatomy. With the advancement of fluorescent protein fusions, the ability to visualize and comprehend how thousands to millions of cells interact with one another to form tissues and organs in three dimensions (xyz) over time (t) is just beginning to be realized and exploited. In this review, we explore recent advances utilizing confocal and multi-photon time-lapse microscopy to capture gene expression, cell behavior, and embryo development. From choosing the appropriate fluorophore, to labeling strategy, to experimental set-up, and data pipeline handling, this review covers the various aspects related to acquiring and analyzing multi-dimensional data sets. These innovative techniques in multi-dimensional imaging and analysis can be applied across a number of fields in time and space including protein dynamics to cell biology to morphogenesis