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Models and Simulations as a Service: Exploring the Use of Galaxy for Delivering Computational Models.

ABSTRACT: We describe the ways in which Galaxy, a web-based reproducible research platform, can be used for web-based sharing of complex computational models. Galaxy allows users to seamlessly customize and run simulations on cloud computing resources, a concept we refer to as Models and Simulations as a Service (MaSS). To illustrate this application of Galaxy, we have developed a tool suite for simulating a high spatial-resolution model of the cardiac Ca(2+) spark that requires supercomputing resources for execution. We also present tools for simulating models encoded in the SBML and CellML model description languages, thus demonstrating how Galaxy's reproducible research features can be leveraged by existing technologies. Finally, we demonstrate how the Galaxy workflow editor can be used to compose integrative models from constituent submodules. This work represents an important novel approach, to our knowledge, to making computational simulations more accessible to the broader scientific community.

SUBMITTER: Walker MA

PROVIDER: S-EPMC4788737 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Models and Simulations as a Service: Exploring the Use of Galaxy for Delivering Computational Models.

Walker Mark A MA Madduri Ravi R Rodriguez Alex A Greenstein Joseph L JL Winslow Raimond L RL

Biophysical journal 20160301 5

We describe the ways in which Galaxy, a web-based reproducible research platform, can be used for web-based sharing of complex computational models. Galaxy allows users to seamlessly customize and run simulations on cloud computing resources, a concept we refer to as Models and Simulations as a Service (MaSS). To illustrate this application of Galaxy, we have developed a tool suite for simulating a high spatial-resolution model of the cardiac Ca(2+) spark that requires supercomputing resources f ...[more]

PMID: 26958881

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Project description:Computational modeling and simulation have become essential tools in the quest to better understand the brain's makeup and to decipher the causal interrelations of its components. The breadth of biochemical and biophysical processes and structures in the brain has led to the development of a large variety of model abstractions and specialized tools, often times requiring high performance computing resources for their timely execution. What has been missing so far was an in-depth analysis of the complexity of the computational kernels, hindering a systematic approach to identifying bottlenecks of algorithms and hardware. If whole brain models are to be achieved on emerging computer generations, models and simulation engines will have to be carefully co-designed for the intrinsic hardware tradeoffs. For the first time, we present a systematic exploration based on analytic performance modeling. We base our analysis on three in silico models, chosen as representative examples of the most widely employed modeling abstractions: current-based point neurons, conductance-based point neurons and conductance-based detailed neurons. We identify that the synaptic modeling formalism, i.e. current or conductance-based representation, and not the level of morphological detail, is the most significant factor in determining the properties of memory bandwidth saturation and shared-memory scaling of in silico models. Even though general purpose computing has, until now, largely been able to deliver high performance, we find that for all types of abstractions, network latency and memory bandwidth will become severe bottlenecks as the number of neurons to be simulated grows. By adapting and extending a performance modeling approach, we deliver a first characterization of the performance landscape of brain tissue simulations, allowing us to pinpoint current bottlenecks for state-of-the-art in silico models, and make projections for future hardware and software requirements.

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Dataset Information

Models and Simulations as a Service: Exploring the Use of Galaxy for Delivering Computational Models.

Publications

Models and Simulations as a Service: Exploring the Use of Galaxy for Delivering Computational Models.

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