Robust scientific methods require the exploration of the parameter space of a system (some of which can be run in parallel on distributed resources), and may involve complete state space exploration, experimental design, or numerical optimization techniques. Many-Task Computing (MTC) provides a framework for performing robust design, because it supports the execution of a large number of otherwise independent processes. Further, scientific workflow engines facilitate the specification and execution of complex software pipelines, such as those found in real science and engineering design problems. However, most existing workflow engines do not support a wide range of experimentation techniques, nor do they support a large number of independent tasks. In this paper, we discuss Nimrod/K—a set of add in components and a new run time machine for a general workflow engine, Kepler. Nimrod/K provides an execution architecture based on the tagged dataflow concepts, developed in 1980s for highly parallel machines. This is embodied in a new Kepler "Director” that supports many-task computing by orchestrating execution of tasks on on clusters, Grids, and Clouds. Further, Nimrod/K provides a set of "Actors” that facilitate the various modes of parameter exploration discussed above. We demonstrate the power of Nimrod/K to solve real problems in cardiac science.

Modern chemistry involves a mix of experimentation and computer-supported theory. Historically, these skills have been provided by different groups, and range from traditional “wet” laboratory science to advanced numerical simulation. This paper discusses the application of advanced e-Science software tools to electrochemistry research and involves collaboration between laboratories at Monash and Oxford Universities. In particular, we show how the Nimrod/OK tool can be used to automate the estimation of electrochemical parameters in Fourier transformed voltammetry. Replacing an ad-hoc manual process with e-Science tools both accelerates the process and produces more accurate solutions. In this work much attention was given to the role of the scientist user. During the research, Nimrod/K (on which Nimrod/OK is built) was extended to shield that user from technical details of the grid infrastructure, a new system of file management and grid abstraction has been incorporated.

In recent years there has been a great deal of interest in "scientific workflows". These allow scientists to specify large computational experiments involving a range of different activities, such as data integration, modelling and analysis, and visualization, to name a few. Activities can be composed, often using a graphical programming environment, so that the output of one stage can be passed as input to the next, forming a pipeline of arbitrary complexity. Scientific workflows have been used to great effect in a number of different disciplines including computational chemistry, ecology and bioinformatics.

Many important and fundamental questions in biology and biochemistry can be better understood through investigations performed at the protein-ligand or drugreceptor level. A variety of techniques have been used over the years, and it is an area of active research. In this paper we illustrate an approach that leverages a number of different computational chemistry approaches, and combines these with non-linear optimization algorithms and grid based high performance computing platforms. The result is a very flexible, high performance method of evaluating protein-ligand interaction algorithms. We illustrate the approach by evaluating a hybrid molecular modeling and quantum theoretical based algorithm.

In this paper we describe the Nimrod/O design optimization tool, and its application in computational fluid dynamics. Nimrod/O facilitates the use of an arbitrary computational model to drive an automatic optimization process. This means that the user can parameterise an arbitrary problem, and then ask the tool to compute the parameter values that minimize or maximise a design objective function. The paper describes the Nimrod/O system, and then discusses a case study in the evaluation of an aerofoil problem. The problem involves computing the shape and angle of attack of the aerofoil that maximises the lift to drag ratio. The results show that our general approach is extremely flexible and delivers better results than a program that was developed specifically for the problem. Moreover, it only took us a few hours to set up the tool for the new problem and required no software development.