Scientific Visualization as a Microservice

Raji, Mohammad; Hota, Alok; Hobson, Tanner; Huang, Jian

doi:10.1109/tvcg.2018.2879672

Cited by 14 publications

(11 citation statements)

References 22 publications

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“…The big data revolution is providing enormously large, incredibly rich, and highly complex data volumes that impose extremely challenging demands on traditional visualization approaches (see e.g. [9,14]). The demands to address are efficiency, i.e.…”

Section: Scientific Visualization Challengesmentioning

confidence: 99%

“…The space community includes astrophysicists and planetary scientists, who are facing a data explosion revolution fuelled by an increasing number of planetary exploration missions (e.g., the Perseverance 12 rover on Mars) and the upcoming deployment of new state of the art observing facilities (e.g., the Square Kilometre Array -SKA, 13 the Vera C. Rubin Observatory, 14 or the James Webb Space Telescope -JWST 15 ). These instruments are expected to produce overwhelming amounts of data volumes, by mapping solar system bodies with an unprecedented detail, or performing new all-sky surveys with unparalleled sensitivity and angular resolution [20].…”

Section: Space Services Technical Challengesmentioning

confidence: 99%

“…https://mars.nasa.gov/mars2020/ 13 https://www.skatelescope.org14 https://www.lsst.org/ 15 https://www.jwst.nasa.gov/ 16 https://ivoa.net 17 https://www.ivoa.net/documents/TAP/…”

mentioning

confidence: 99%

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Scientific Visualization on the Cloud: the NEANIAS Services towards EOSC Integration

et al. 2022

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NEANIAS is a research and innovation action project funded by the European Union under the Horizon 2020 program. The project addresses the challenge of prototyping novel solutions for the underwater, atmospheric and space research communities, creating a collaborative research ecosystem, and contributing to the effective materialization of the European Open Science Cloud (EOSC). NEANIAS drives the co-design, implementation, delivery, and integration into EOSC of innovative thematic and core services, derived from state-of-the-art assets and practices in the target scientific communities. We present the overall NEANIAS ecosystem architecture, with an emphasis on its core visualization services, detailing their specifications and software development plan, and focusing on the underpinning service-oriented architecture for their delivery. We report on the underlying ideas and guiding principles for designing such visualization services, outlining their current release status and future development roadmaps towards Technological Readiness Level (TRL) 8 maturity and EOSC integration.

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Section: Scientific Visualization Challengesmentioning

confidence: 99%

Section: Space Services Technical Challengesmentioning

confidence: 99%

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Scientific Visualization on the Cloud: the NEANIAS Services towards EOSC Integration

et al. 2022

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“…These tools allow sharing, editing, and storing of scientific visualizations through the web. Reference [16] presents a microservice based architecture that uses cloud computing on Amazon Web Services (AWS) for server computation that enable interactive visualizations embedded in web. Web based generated visualization of high dimensional data with the tool SPOT was recently described [17].…”

Section: Background Literature On Web Based Visualizationmentioning

confidence: 99%

QMwebJS—An Open Source Software Tool to Visualize and Share Time-Evolving Three-Dimensional Wavefunctions

et al. 2020

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Numerical simulation experiments are of great importance for research and education in Physics. They can be greatly aided by proper graphical representations, especially for spatio-temporal dynamics. In this contribution, we describe and provide a novel Javascript-based library and cloud microservice—QMwebJS—for the visualization of the temporal evolution of three-dimensional distributions. It is an easy to use, web-based library for creating, editing, and exporting 3D models based on the particle sampling method. Accessible from any standard browser, it does not require downloads or installations. Users can directly share their work with other students, teachers or researchers by keeping their models in the cloud and allowing for interactive viewing of the spatio-temporal solutions. This software tool was developed to support quantum mechanics teaching at an undergraduate level by plotting the spatial probability density distribution given by the wavefunction, but it can be useful in different contexts including the study of nonlinear waves.

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“…The following cloud computer service platforms are compared below:  Google Cloud Platform;  Microsoft Azure;  Amazon Web Services. In spite various visualization services are already provided in the cloud computing platforms, for example on Amazon [5], this does not allow users to stay completely in the frames of their customary lighting simulation software.…”

Section: Introductionmentioning

confidence: 99%

Towards Hardware OpenGL Support in Cloud Computing

Denisov¹,

Kalugina²

2021

Proceedings of the 31th International Conference on Computer Graphics and Vision. Volume 2

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Modern realistic computer graphics applications, such as physically accurate lighting simulation systems, require a lot of computer power for images generation. Usage of the resources of cloud computing platforms for such calculations allows to avoid additional expenses for purchase and maintenance of own computer farms. However often such simulation systems use OpenGL for 3D images display, for example during scene preparation and modification. Since cloud-based virtual machines had only software (that is, slow) OpenGL display support, it was not convenient for the users to work with their habitual computer graphics applications in such environments, and typical workflow was to prepare all data on local computer and then execute simulation in the cloud service (usually using distributed processing). Recently several cloud computer service providers started to suggest users the option of hardware (GPU-based) OpenGL support in their cloud virtual machines. This article is devoted to the investigation of hardware OpenGL display options, suggested by various providers of cloud computing services, and their comparison. Available types of hardware GPU were checked and compared, along with the conditions for their usage.

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Scientific Visualization as a Microservice

Cited by 14 publications

References 22 publications

Scientific Visualization on the Cloud: the NEANIAS Services towards EOSC Integration

Scientific Visualization on the Cloud: the NEANIAS Services towards EOSC Integration

QMwebJS—An Open Source Software Tool to Visualize and Share Time-Evolving Three-Dimensional Wavefunctions

Towards Hardware OpenGL Support in Cloud Computing

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