Using Parallel Isosurface Extraction in Superficial Molecular Modeling

Merelli, Ivan; Milanesi, Luciano; Agostino, D.D.; Clematis, Andrea; Vanneschi, Marco; Danelutto, Marco

doi:10.1109/dfma.2005.51

Cited by 7 publications

(4 citation statements)

References 12 publications

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“…In particular, it has been used to program computational chemistry applications [19], image processing applications [15], bioinformatics applications [32] and different applications processing SAR satellite images as well as to run several benchmarking applications including data mining code [18] and numerical kernels. The typical results achieved are those shown in Fig.…”

Section: Performance Resultsmentioning

confidence: 99%

High level Grid programming with ASSIST*

Aldinucci¹,

Coppola²,

Danelutto³

et al. 2006

CMST

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Abstract:The development of efficient Grid applications usually requires writing huge portions of code directly at the level of abstraction provided by the underlying Grid middleware. In this work we discuss an alternative approach, raising the level of abstraction used when programming Grid applications. Our approach requires programmers just to describe in a qualitative way the kind of parallelism they want to express. Then, compiler tools, loader tools and run time system take complete care of running the application on a Grid target architecture. This allows to move most of the cumbersome tasks related to Grid targeting and management from programmer responsibility to tools. This paper introduces the structured parallel programming environment ASSIST, whose design is aimed at raising the level of abstraction in Grid programming and discusses how it can support transparent Grid programming while implementing Grid adaptivity.

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Section: Performance Resultsmentioning

confidence: 99%

High level Grid programming with ASSIST*

Aldinucci¹,

Coppola²,

Danelutto³

et al. 2006

CMST

Self Cite

View full text Add to dashboard Cite

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“…3). The extraction is carried out using the Marching Cubes algorithm [19], that allows to define a triangular mesh for any kind of surface topology starting from its volumetric description.…”

Section: Methodsmentioning

confidence: 99%

High performance workflow implementation for protein surface characterization using grid technology

et al. 2005

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Background: This study concerns the development of a high performance workflow that, using grid technology, correlates different kinds of Bioinformatics data, starting from the base pairs of the nucleotide sequence to the exposed residues of the protein surface. The implementation of this workflow is based on the Italian Grid.it project infrastructure, that is a network of several computational resources and storage facilities distributed at different grid sites.

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“…Surface: this step represents the input of our analysis. In our case the molecular surface representation is computed starting from its atomic coordinates (many algorithms for this stage are available (see, for example, Sanner et al, 1995;Merelli et al, 2005;Cepas Quin˜onero et al, 2011) and provided in the form of a triangular mesh (see Merelli et al, 2005 for more details). Shape conversion: the input surface representation is converted in a corresponding set of images of local description (and related oriented points).…”

Section: Macromolecular Surface Analysismentioning

confidence: 99%

Porting bioinformatics applications from grid to cloud: A macromolecular surface analysis application case study

Merelli

Cozzi

Ronchieri³

et al. 2015

The International Journal of High Performance Computing Applica

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In this paper we describe our experience in exploiting different cloud-based environments for an actual use case taken from the bioinformatics domain – the molecular surfaces analysis - that identifies similarities and possible complementarities in the protein surfaces. The analysis of macromolecular surfaces is important since protein surface conformations drive many biological reactions. We developed a workflow that performs the macromolecular surfaces analysis and provides interesting results from a scientific point of view. An important issue is represented by the fact that it is highly compute-intensive, therefore it cannot be run on a single CPU system for meaningful use cases and a parallel infrastructure is required to obtain reasonable execution time. For a decade grid infrastructures have represented suitable solutions to achieve cost effective computational power for Bioinformatics applications. However, these solutions do not offer an adequate customisation of the computational environment (e.g. installing databases and configuring virtual network) due to the rigid organisation of the storage and computational sites. Running applications on customised machines obtained by user-defined images simplifies the computing model, decreases the failure rates and therefore reduces waiting times for production analysis with respect to the canonical grid computations. For these reasons a cloud-based approach is more suitable than a pure grid paradigm. We experimented using two cloud-based approaches, based on the Worker Node On Demand Service and on OpenStack, to run the molecular surfaces analysis use case and we compared the results in terms of performance, efficiency and efforts to build the computing model with respect to grid computing.

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Using Parallel Isosurface Extraction in Superficial Molecular Modeling

Cited by 7 publications

References 12 publications

High level Grid programming with ASSIST*

High level Grid programming with ASSIST*

High performance workflow implementation for protein surface characterization using grid technology

Porting bioinformatics applications from grid to cloud: A macromolecular surface analysis application case study

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