Michele Guidolin

Battle of the Water Networks II

The Battle of the Water Networks II (BWN-II) is the latest of a series of competitions related to the design and operation of water distribution systems (WDSs) undertaken within the Water Distribution Systems Analysis (WDSA) Symposium series. The BWN-II problem specification involved a broadly defined design and operation problem for an existing network that has to be upgraded for increased future demands, and the addition of a new development area. The design decisions involved addition of new and parallel pipes, storage, operational controls for pumps and valves, and sizing of backup power supply. Design criteria involved hydraulic, water quality, reliability, and environmental performance measures. Fourteen teams participated in the Battle and presented their results at the 14th Water Distribution Systems Analysis conference in Adelaide, Australia, September 2012. This paper summarizes the approaches used by the participants and the results they obtained. Given the complexity of the BWN-II problem and the innovative methods required to deal with the multiobjective, high dimensional and computationally demanding nature of the problem, this paper represents a snap-shot of state of the art methods for the design and operation of water distribution systems. A general finding of this paper is that there is benefit in using a combination of heuristic engineering experience and sophisticated optimization algorithms when tackling complex real-world water distribution system design problems

CWSNet: An object-oriented toolkit for water distribution system simulations

In the field of water distribution systems the EPANET 2 toolkit is considered nowadays the industry standard for hydraulic modelling. Unfortunately, the design and programming model of EPANET 2 have some limitations that make any attempt to extend its hydraulic solver, add new functionalities or improve performance difficult to achieve and time consuming. A new software toolkit for water distribution system modelling, CWSNet, is presented. CWSNet is developed in C++ using the object-oriented programming model. The aim is to deliver an open-source substitute for EPANET 2 that obtains numerically comparable results while providing similar or better performance, a higher degree of extensibility, as well as backward compatibility where possible. The idea behind this project is to simplify development and testing of new hydraulic elements (specific types of valves, pumps, etc) and computational algorithms (pressure-driven approaches, etc.) by keeping logically independent parts of the code separate. This also allows the performance and accuracy of new computational methods as well as the use of advanced programming techniques (multi-threading, OpenMP, GPGPU, etc) to be studied without the need for extensive code refactoring. The basic version of CWSNet gives numerically the same results as EPANET 2 for various networks while allowing the following: (a) to change the topology of the network at runtime; (b) to run different simulations of the same network or different networks in parallel (thread-safe); (c) to easily change the mathematical model and other particulars behind the hydraulic simulation engine; (d) to allow a high degree of customisation of the output of an extended period simulation. The CWSNet software capabilities are demonstrated using several examples. The results obtained demonstrate the effectiveness and efficiency of the proposed approach.

Experiments with SmartGridSolve: Achieving higher performance by improving the GridRPC model

The paper presents SmartGridSolve, an extension of GridSolve, the programming system for high performance computing. The extension is aimed at higher performance of Grid applications by providing the functionality for collective mapping of a group of tasks on to a network topology that is fully connected. This functionality was achieved with only a minor addition to the GridRPC API. The key to the implementation of collective mapping was to separate the mapping of tasks from their execution which is one atomic operation in the GridRPC model of GridSolve. This paper demonstrates the performance gained by collective mapping with a real-life astrophysical experiment. The presented results show a significant speedup of 2.17 executing this application on a small network of two servers.

Grid-enabled hydropad: A scientific application for benchmarking GridRPC-based programming systems

GridRPC is a standard API that allows an application to easily interface with a Grid environment. It implements a remote procedure call with a single task map and client-server communicationmodel. In addition to non-performance-related benefits, scientific applications having large computation and small communication tasks can also obtain important performance gains by being implemented in GridPRC. However, such convenient applications are not representative of the majority of scientific applications and therefore cannot serve as fair benchmarks for comparison of the performance of different GridRPC-based systems. In this paper, we present Hydropad, a real life astrophysical simulation, which is composed of tasks that have a balanced ratio between computation and communication. While Hydropad is not the ideal application for performance benefits from its implementation with GridRPC middleware, we show how even its performance can be improved by using GridSolve and SmartGridSolve. We believe that the Grid-enabled Hydropad is a good candidate application to benchmark GridRPC-based programming systems in order to justify their use for high performance scientific computing.

How Algorithm Definition Language (ADL) improves the performance of SmartGridSolve applications

In this paper, we study the importance of languages for the specification of algorithms in high performance Grid computing. We present one such language, the Algorithm Definition Language (ADL), designed and implemented for the use in conjunction with SmartGridSolve. We demonstrate that the use of this type of language can significantly improve the performance of Grid applications. We discuss how ADL can be used to improve the execution of some typical algorithms that use conditional statements, iterative computations and adaptive methods. We present experimental results demonstrating significant performance gains due to the use of ADL.