FabSim: Facilitating computational research through automation on large-scale and distributed e-infrastructures ✩

Abstract We present FabSim, a toolkit developed to simplify a range of computational tasks for researchers in diverse disciplines. FabSim is flexible, adaptable, and allows users to perform a wide range of tasks with ease. It also provides a systematic way to automate the use of resources, including HPC and distributed machines, and to make tasks easier to repeat by recording contextual information. To demonstrate this, we present three use cases where FabSim has enhanced our research productivity. These include simulating cerebrovascular bloodflow, modelling clay-polymer nanocomposites across multiple scales, and calculating ligand–protein binding affinities. Program summary Program title: FabSim Catalogue identifier: AFAO_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AFAO_v1_0.html Program obtainable from: CPC Programme Library, Queen’s University, Belfast, N. Ireland Licensing provisions: BSD 3-Clause No. of lines in distributed program, including test data, etc.: 268282 No. of bytes in distributed program, including test data, etc.: 2791792 Distribution format: tar.gz Programming language: Python. Computer: PC or Mac. Operating system: Unix, OSX. RAM: 1 Gbytes Classification: 3, 4, 6.5. External routines: NumPy, SciPy, Fabric (1.5 or newer), PyYaml Nature of problem: Running advanced computations using remote resources is an activity that requires considerable time and human attention. These activities, such as organizing data, configuring software and setting up individual runs often vary slightly each time they are performed. To lighten this burden, we required an approach that introduced little burden of its own to set up and adapt, beyond which very substantial productivity ensues. Solution method: We present a toolkit which helps to simplify and automate the activities which surround computational science research. FabSim is aimed squarely at the experienced computational scientist, who can use the command line interface and a system of modifiable content to quickly automate sets of research tasks. Restrictions: FabSim relies on a command-line interface, and assumes some level of scripting knowledge from the user. Unusual features: FabSim has a proven track record of being easy to adapt. It has already been extensively adapted to facilitate leading research in the modelling of bloodflow, nanomaterials, and ligand–protein binding. Running time: FabSim can be used interactively, typically requiring a few seconds to perform a basic task.