ReSHAPE: A Framework for Dynamic Resizing and Scheduling of Homogeneous Applications in a Parallel Environment

Applications in science and engineering often require huge computational resources for solving problems within a reasonable time frame. Parallel supercomputers provide the computational infrastructure for solving such problems. A traditional application scheduler running on a parallel cluster only supports static scheduling where the number of processors allocated to an application remains fixed throughout the lifetime of execution of the job. Due to the unpredictability in job arrival times and varying resource requirements, static scheduling can result in idle system resources thereby decreasing the overall system throughput. In this paper we present a prototype framework called ReSHAPE, which supports dynamic resizing of parallel MPI applications executed on distributed memory platforms. The framework includes a scheduler that supports resizing of applications, an API to enable applications to interact with the scheduler, and a library that makes resizing viable. Applications executed using the ReSHAPE scheduler framework can expand to take advantage of additional free processors or can shrink to accommodate a high priority application, without getting suspended. In our research, we have mainly focused on structured applications that have two-dimensional data arrays distributed across a two-dimensional processor grid. The resize library includes algorithms for processor selection and processor mapping. Experimental results show that the ReSHAPE framework can improve individual job turn-around time and overall system throughput.Comment: 15 pages, 10 figures, 5 tables Submitted to International Conference on Parallel Processing (ICPP'07

Prevention of Recurrent Systemic Embolism with Anticoagulants in Patients with Rheumatic Heart Disease

Results are reported of long-term anticoagulant treatment in a group of 90 patients with rheumatic heart disease who had systemic embolism. Compared to the reported incidence of recurrent systemic embolism in patients not given anticoagulant drugs, such therapy remarkably lowers the risk of such occurrences. Complications from this treatment in the reported patients were minimal

Hemp Concrete: A Sustainable Green Material for Conventional Concrete

Concrete is one of the most important building material and day by day theutilization of concrete is increasing to meet the infrastructure developmentrequirement. On one hand it is unavoidable but some alternative to beexplored to reduce the global environmental impact caused by the concrete.To overcome this from the last decade the world is looking towards thefact of sustainability due to rapid industrialization. The growth in theconstruction industry increased the demand of concrete as constructionmaterial. This concrete produces significant amount of greenhouse emissionin the environment. There is a need to find an alternative solution tominimize the greenhouse emission emitted from the concrete manufacturingplant.Hempcrete is a building material prepared from hemp yarns, lime andwater. This composite material has several beneficial properties like lowin cost, easily available, thermal and acoustic insulation, low density andsustainable cause of no adverse impact of carbon footprint on production.In this study the properties and several benefits of the hempcrete werediscussed in detail

Rolling Element Bearing Condition Monitoring using Filtered Acoustic Emission

The defect present in the bearing of a rolling element may affect the performance of the rotating machinery and may reduce its efficiency. For this reason the condition monitoring of a rolling element bearing is very essential. So many measuring parameters are there to diagnose the fault in a rolling element bearing. Acoustic signature monitoring is one of them. Every rolling element bearing has its own acoustic signature when it is in healthy condition and when the bearing get defected then there is a change in its original acoustic signature. This change in acoustic signature can be monitored and analyzed to detect the fault present in the bearing. But the noise present in the acquired acoustic signal may affect the analysis. So the noisy acoustic signal must be filtered before the analysis. In this work the experiment is performed in two stages. In first stage the filtration of the acquired acoustic signal is done by employing the active noise cancellation (ANC) filtering techniques. In second stage the filtered signal is used for the further analysis. For the analysis initially the static analysis is done and then the frequency and the time-frequency analysis is done to diagnose the defect in the bearing. From all the three analysis the information about the defect present in the bearing is well detected

CDM as a Solution for the Present World Energy Problems (An Overview with Respect to the Building and Construction Sector)

One of the important responses of Kyoto Protocol towards mitigation of global warming is the Clean Development Mechanism (CDM), which has garnered large emphasis amidst the global carbon market in terms of Certified Emission Reductions (CERs). While CDM aims to achieve sustainable development in the energy production and its consumption in developing countries, the results achieved through its implementation are still uncertain. Presently, the domestic and commercial buildings are responsible for more than one third of the total conventional energy use and associated greenhouse gas emissions. The Inter-governmental Panel on Climate Change (IPCC) stated that, the building sector has the largest potential for significantly reducing greenhouse gas emissions. This paper envisages the important aspects such as, the non-inclusion of construction sector projects in CDM and its reasons, the role of energy efficiency buildings in the energy conservation arena and the new challenges being faced, while implementing the CDM portfolio in building energy sector

A Meta Model for Domestic Energy Consumption

Prediction of energy consumption particularly in micro level is of vital importance in terms of energy planning and also implementation of any Clean Development Mechanism (CDM) activities that has become the order of the world today. It may be difficult to model household energy consumption using conventional methods such as time series forecasting due to many influencing factors. This paper presents a step wise regression model for forecasting domestic energy consumption based on micro level household survey data collected from Kerala, a state in southern part of India. The analysis of the data reveals significant influence of socio-economic, demographic, geographic, and family attributes upon total household energy requirements. While a wide variation in the pattern of energy requirements across the domestic sector belonging to different expenditure classes, per capita income level can be identified as the most important explanatory variable influencing variation in energy requirements. The models developed also demonstrates the influence of per capita land area, residential area among the higher income group while average age and literacy forms significant variables among the lower income group. Keywords: Meta Model; Consumption Pattern; Domestic Energy Requirement JEL classifications: E2; Q

Operational framework based on modeling languages to support product repository implementation.

Part 3: Tools and MethodologiesInternational audienceEmbracing Product Lifecycle Management approach involves integrating a product repository in the company information system. From customer's needs to disposal stage, several product representations exist. The product repository purpose is to secure consistency of one product representation with the others. This paper presents an operational modeling framework that supports product repository implementation. In order to ensure consistency, this framework identifies correspondences between entities of languages (“trade” languages and standard languages). The presented concepts are illustrated with correspondences between language entities of product designed and productplanned to be built Bills of Materials

Long-term ambient air-stable cubic CsPbBr3 perovskite quantum dots using molecular bromine

We report unprecedented phase stability of cubic CsPbBr3 quantum dots in ambient air obtained by using Br2 as halide precursor. Mechanistic investigation reveals the decisive role of temperature-controlled in situ generated, oleylammonium halide species from molecular halogen and amine for the long term stability and emission tunability of CsPbX3 (X = Br, I) nanocrystals

Development of a Modular Biosensor System for Rapid Pathogen Detection

Progress in the field of pathogen detection relies on at least one of the following three qualities: selectivity, speed, and cost-effectiveness. Here, we demonstrate a proof of concept for an optical biosensing system for the detection of the opportunistic human pathogen Pseudomonas aeruginosa while addressing the abovementioned traits through a modular design. The biosensor detects pathogen-specific quorum sensing molecules and generates a fluorescence signal via an intracellular amplifier. Using a tailored measurement device built from low-cost components, the image analysis software detected the presence of P. aeruginosa in 42 min of incubation. Due to its modular design, individual components can be optimized or modified to specifically detect a variety of different pathogens. This biosensor system represents a successful integration of synthetic biology with software and hardware engineering