Noam Weingarten

Parameter Sweep Workflows for Modelling Carbohydrate Recognition

Carbohydrate recognition is a phenomenon critical to a number of biological functions in humans. Understanding the dynamic behaviour of oligosaccharides should help in the discovery of the mechanisms which lead to specific and selective recognition of carbohydrates by proteins. Computer programs which can provide insight into such biological recognition processes have significant potential to contribute to biomedical research if the results of the simulation can prove consistent with the outcome of conventional wet laboratory experiments. In order to validate these simulation tools and support their wider uptake by the bio-scientist research community, high-level easy to use integrated environments are required to run massively parallel simulation workflows. This paper describes how the ProSim Science Gateway, based on the WS-PGRADE Grid portal, has been created to execute and visualise the results of complex parameter sweep workflows for modelling carbohydrate recognition.

Quantum chemical meta-workflows in MoSGrid

Quantum chemical workflows can be built up within the science gateway Molecular Simulation Grid. Complex workflows required by the end users are dissected into smaller workflows that can be combined freely to larger meta‐workflows. General quantum chemical workflows are described here as well as the real use case of a spectroscopic analysis resulting in an end‐user desired meta‐workflow. All workflow features are implemented via Web Services Parallel Grid Runtime and Developer Environment and submitted to UNICORE. The workflows are stored in the Molecular Simulation Grid repository and ported to the SHIWA repository. Copyright

Traffic Simulation in P-Grade as a Grid Service

Grid Execution Management for Legacy Code Architecture (GEMLCA) is a general architecture to deploy existing legacy applications as Grid services without re-engineering the original code. Using GEMLCA from the P-Grade portal, legacy code programs can be accessed as Grid services and even participate in complex Grid workflows. The parallel version of MadCity, a discrete time-based traffic simulator, was created using P-Grade. This paper describes how MadCity is offered as a Grid service using GEMLCA and how this solution is embedded into the P-Grade portal.

Meta-Metaworkflows for Combining Quantum Chemistry and Molecular Dynamics in the MoSGrid Science Gateway

MoSGrid (Molecular Simulation Grid) is a user-friendly and highly efficient science gateway which contains three domains for the different methodologies used in chemistry: quantum chemistry, molecular dynamics, and docking. Workflows are implemented by using the WS-PGRADE technology. By adding an abstraction layer, we are able to develop meta-metaworkflows for quantum chemical applications and a combination between quantum chemical and molecular dynamics applications. This approach allows researchers to easily and more quickly create highly complex workflows allowing them to shorten the time-to-result considerably.

A Formal Approach to Support Interoperability in Scientific Meta-workflows

Scientific workflows orchestrate the execution of complex experiments frequently using distributed computing platforms. Meta-workflows represent an emerging type of such workflows which aim to reuse existing workflows from potentially different workflow systems to achieve more complex and experimentation minimizing workflow design and testing efforts. Workflow interoperability plays a profound role in achieving this objective. This paper is focused at fostering interoperability across meta-workflows that combine workflows of different workflow systems from diverse scientific domains. This is achieved by formalizing definitions of meta-workflow and its different types to standardize their data structures used to describe workflows to be published and shared via public repositories. The paper also includes thorough formalization of two workflow interoperability approaches based on this formal description: the coarse-grained and fine-grained workflow interoperability approach. The paper presents a case study from Astrophysics which successfully demonstrates the use of the concepts of meta-workflows and workflow interoperability within a scientific simulation platform.

A Definition and Analysis of the Role of Meta-workflows in Workflow Interoperability

Scientific workflows orchestrate the execution of complex experiments on high performance computing platforms. Meta-workflows represent an emerging type of such workflows which aim to integrate multiple embedded workflows from potentially different workflow systems to achieve complex experimentation. Workflow interoperability plays a profound role in achieving this objective. This paper is focused at formalizing definitions of different types of workflows and meta-workflows to facilitate improved understanding and interoperability. It also includes thorough formalization of the coarse grained workflow interoperability approach highlighting the role of workflow systems. The paper presents a case study from Heliophysics which successfully demonstrates the use of technologies developed to realize the concepts of meta-workflows and workflow interoperability within a science gateway environment.

A Grid Implementation for Profiling Hospitals Based on Patient Readmissions

Generally, high level of readmission is associated with poor patient care, hence its relation to the quality of care is plausible. Frequent patient readmissions have personal, financial and organisational consequences. This has motivated healthcare commissioners in England to use emergency readmission as an indicator in the performance rating framework. A statistical model, known as the multilevel transition model was previously developed, where individual hospitals propensity for first readmission, second readmission, third (and so on) were considered to be measures of performance. Using these measures, we defined a new performance index. During the period 1997 and 2004, the national (England) hospital episodes statistics dataset comprise more than 5 million patient readmissions. Implementing a statistical model using the complete population dataset could possibly take weeks to estimate the parameters. Moreover, it is not statistically sound to utilise the full population dataset. To resolve the problem, we extract 1000 random samples from the original data, where each random sample is likely to lead to differing hospital performance measures. For computational efficiency a Grid implementation of the model is developed. Using a stand-alone computer, it would take approximately 500 hours to estimate 1000 samples, whereas in the Grid implementation, the full 1000 samples were analysed in less than 24 hours. Analysing the output from the full 1000 sample, we noticed that 4 out of the 5 worst performing hospitals treating cancer patients were in London.