scholarly journals A Component Approach to Collaborative Scientific Software Development: Tools and Techniques Utilized by the Quantum Chemistry Science Application Partnership

2008 ◽  
Vol 16 (4) ◽  
pp. 287-296 ◽  
Author(s):  
Joseph P. Kenny ◽  
Curtis L. Janssen ◽  
Mark S. Gordon ◽  
Masha Sosonkina ◽  
Theresa L. Windus
Keyword(s):  
Software Engineering ◽  
Quantum Chemistry ◽  
Large Scale ◽  
Programming Model ◽  
Scientific Software ◽  
Collaborative Development ◽  
Common Component ◽  
Component Approach ◽  
Common Component Architecture ◽  
Science Application

Cutting-edge scientific computing software is complex, increasingly involving the coupling of multiple packages to combine advanced algorithms or simulations at multiple physical scales. Component-based software engineering (CBSE) has been advanced as a technique for managing this complexity, and complex component applications have been created in the quantum chemistry domain, as well as several other simulation areas, using the component model advocated by the Common Component Architecture (CCA) Forum. While programming models do indeed enable sound software engineering practices, the selection of programming model is just one building block in a comprehensive approach to large-scale collaborative development which must also address interface and data standardization, and language and package interoperability. We provide an overview of the development approach utilized within the Quantum Chemistry Science Application Partnership, identifying design challenges, describing the techniques which we have adopted to address these challenges and highlighting the advantages which the CCA approach offers for collaborative development.

scholarly journals Managing Scientific Software Complexity with Bocca and CCA

2008 ◽  
Vol 16 (4) ◽  
pp. 315-327 ◽  
Author(s):  
Benjamin A. Allan ◽  
Boyana Norris ◽  
Wael R. Elwasif ◽  
Robert C. Armstrong
Keyword(s):  
High Performance ◽  
Web Applications ◽  
Scientific Software ◽  
Common Component ◽  
Software Complexity ◽  
Common Component Architecture ◽  
Engineering Practices ◽  
Short Time ◽  
Application Developers ◽  
Glue Code

In high-performance scientific software development, the emphasis is often on short time to first solution. Even when the development of new components mostly reuses existing components or libraries and only small amounts of new code must be created, dealing with the component glue code and software build processes to obtain complete applications is still tedious and error-prone. Component-based software meant to reduce complexity at the application level increases complexity to the extent that the user must learn and remember the interfaces and conventions of the component model itself. To address these needs, we introduce Bocca, the first tool to enable application developers to perform rapid component prototyping while maintaining robust software-engineering practices suitable to HPC environments. Bocca provides project management and a comprehensive build environment for creating and managing applications composed of Common Component Architecture components. Of critical importance for high-performance computing (HPC) applications, Bocca is designed to operate in a language-agnostic way, simultaneously handling components written in any of the languages commonly used in scientific applications: C, C++, Fortran, Python and Java. Bocca automates the tasks related to the component glue code, freeing the user to focus on the scientific aspects of the application. Bocca embraces the philosophy pioneered by Ruby on Rails for web applications: start with something that works, and evolve it to the user's purpose.

scholarly journals A robust-heuristic optimization approach to a green supply chain design with consideration of assorted vehicle types and carbon policies under uncertainty

2021 ◽  
Author(s):  
Zahra Homayouni ◽  
Mir Saman Pishvaee ◽  
Hamed Jahani ◽  
Dmitry Ivanov
Keyword(s):  
Supply Chains ◽  
Large Scale ◽  
Programming Model ◽  
Supply Chain Design ◽  
Heuristic Optimization ◽  
Optimization Approach ◽  
Economic Uncertainty ◽  
Cap And Trade ◽  
Sustainable Logistics ◽  
Goal Programming Model

AbstractAdoption of carbon regulation mechanisms facilitates an evolution toward green and sustainable supply chains followed by an increased complexity. Through the development and usage of a multi-choice goal programming model solved by an improved algorithm, this article investigates sustainability strategies for carbon regulations mechanisms. We first propose a sustainable logistics model that considers assorted vehicle types and gas emissions involved with product transportation. We then construct a bi-objective model that minimizes total cost as the first objective function and follows environmental considerations in the second one. With our novel robust-heuristic optimization approach, we seek to support the decision-makers in comparison and selection of carbon emission policies in supply chains in complex settings with assorted vehicle types, demand and economic uncertainty. We deploy our model in a case-study to evaluate and analyse two carbon reduction policies, i.e., carbon-tax and cap-and-trade policies. The results demonstrate that our robust-heuristic methodology can efficiently deal with demand and economic uncertainty, especially in large-scale problems. Our findings suggest that governmental incentives for a cap-and-trade policy would be more effective for supply chains in lowering pollution by investing in cleaner technologies and adopting greener practices.

Resource Configuration for the Collaborative Development of Product

2012 ◽  
Vol 215-216 ◽  
pp. 540-543
Author(s):  
Fu Hong Zeng ◽  
Lan Hua Zhou
Keyword(s):  
Mobile Phone ◽  
Large Scale ◽  
Collaborative Planning ◽  
Matching Model ◽  
Collaborative Development ◽  
Resource Configuration ◽  
Manufacturing Enterprises

In order to meet the reasonable matching of resource for collaborative development of products in manufacturing enterprises including involvement of suppliers on a large scale, a Generalized Design Resource Pool (GDRP) and It’s Resource Particles (RP) are defined, a multi-project collaborative planning and resource particles constraint-matching model with realization algorithm is presented. Finally, a case of developing mobile phone to an enterprise is presented to verify the effectiveness and feasibility of the presented approach.

An Analysis of Process Characteristics for Developing Scientific Software

2011 ◽  
Vol 23 (4) ◽  
pp. 64-79 ◽  
Author(s):  
Diane Kelly
Keyword(s):  
Software Engineering ◽  
Software Development ◽  
Professional Training ◽  
Scientific Software ◽  
Development Environment ◽  
Engineering Development ◽  
Development Processes ◽  
Agile Software ◽  
Development Methods ◽  
Software Development Methods

The development of scientific software is usually carried out by a scientist who has little professional training as a software developer. Concerns exist that such development produces low-quality products, leading to low-quality science. These concerns have led to recommendations and the imposition of software engineering development processes and standards on the scientists. This paper utilizes different frameworks to investigate and map characteristics of the scientific software development environment to the assumptions made in plan-driven software development methods and agile software development methods. This mapping exposes a mismatch between the needs and goals of scientific software development and the assumptions and goals of well-known software engineering development processes.

Parallelization of a Commercial Streamline Simulator and Performance on Practical Models

2010 ◽  
Vol 13 (03) ◽  
pp. 383-390 ◽  
Author(s):  
R.P.. P. Batycky ◽  
M.. Förster ◽  
M.R.. R. Thiele ◽  
K.. Stüben
Keyword(s):  
Large Scale ◽  
Programming Model ◽  
Scaling Law ◽  
Independent Solution ◽  
Parallel Execution ◽  
Water Model ◽  
Test Machine ◽  
Multicore Architectures ◽  
Streamline Simulation ◽  
Run Time

Summary We present the parallelization of a commercial streamline simulator to multicore architectures based on the OpenMP programming model and its performance on various field examples. This work is a continuation of recent work by Gerritsen et al. (2009) in which a research streamline simulator was extended to parallel execution. We identified that the streamline-transport step represents approximately 40-80% of the total run time. It is exactly this step that is straightforward to parallelize owing to the independent solution of each streamline that is at the heart of streamline simulation. Because we are working with an existing large serial code, we used specialty software to quickly and easily identify variables that required particular handling for implementing the parallel extension. Minimal rewrite to existing code was required to extend the streamline-transport step to OpenMP. As part of this work, we also parallelized additional run-time code, including the gravity-line solver and some simple routines required for constructing the pressure matrix. Overall, the run-time fraction of code parallelized ranged from 0.50 to 0.83, depending on the transport physics being considered. We tested our parallel simulator on a variety of large models including SPE 10, Forties-a UK oil/water model, Judy Creek-a Canadian waterflood/water-alternating-gas (WAG) model, and a South American black-oil model. We noted overall speedup factors from 1.8 to 3.3x for eight threads. In terms of real time, this implies that large-scale streamline simulation models as tested here can be simulated in less than 4 hours. We found speedup results to be reasonable when compared with Amdahl's ideal scaling law. Beyond eight threads, we observed minimal speedups because of memory bandwidth limits on our test machine.

Large-Scale Visualization Projects for Teaching Software Engineering

2012 ◽  
Vol 32 (4) ◽  
pp. 14-19 ◽  
Author(s):  
Christoph Moller ◽  
Guido Reina ◽  
Michael Burch ◽  
Daniel Weiskopf
Keyword(s):  
Software Engineering ◽  
Large Scale
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