Abstract
This paper presents a new unified approach to adapt scientific visualization systems to third-party solvers implemented on different software and hardware platforms. This approach allows building multiplatform visualization systems, enables automatic conversion of input and output data from any solver into a rendering-compatible format, and provides real-time generation of high-quality images. The automated adaptation of visualization systems to third-party solvers is based on ontological engineering methods. Multiplatform portability is provided by the automatic generation of a graphical user interface (GUI) for each particular operating system and by preprocessing the data to be rendered by using heuristic-based tools, which ensures compatibility with different hardware and software platforms, including desktop computers and mobile devices. In addition, an original anti-aliasing algorithm is proposed to ensure high quality of resulting images. Based on the proposed approach, a multiplatform scientific visualization system called SciVi is developed, which is successfully used for solving various real-world scientific visualization problems from different application domains.
Similar content being viewed by others
References
Vasil’ev, V.R., Voloboi, A.G., V’yukova, N.I., and Galaktionov, V.A., Context visualization of spatial data, Inf. Tekhnol. Vychisl. Sist., 2004, no. 4, pp. 25–34.
Ryabinin, K. and Chuprina, S., Development of multiplatform adaptive rendering tools to visualize scientific experiments, Procedia Comput. Sci., 2014, vol. 29, pp. 1825–1834.
Bondarev, A.E. and Galaktionov, V.A., Multidimensional analysis in multiparametric optimization problems with the use of visualization methods, Nauchn. Vizualizatsiya, 2012, vol. 4, no. 2, pp. 1–13.
Ryabinin, K. and Chuprina, S., Development of ontology-based multiplatform adaptive scientific visualization system, J. Comput. Sci., 2015, vol. 10, pp. 370–381.
Gavrilova, T.A. and Khoroshevskii, V.F., Bazy znanii intellektual’nykh sistem (Knowledge Bases for Intelligent Systems), St. Petersburg: Piter, 2001.
Richardson, T., Stafford-Fraser, Q., Wood, K.R., and Hopper, A., Virtual network computing, IEEE Internet Comput., 1998, vol. 2, no. 1, pp. 33–38.
Lizandra, M.C.J., Graphic libraries for Windows programming, XRDS, 2000, vol. 6, no. 4, pp. 14–18.
Lottes, T., Fast Approximate Anti-Aliasing. NVidia, 2009. http://developer.download.nvidia.com/assets/gamedev/files/sdk/11/FXAA_WhitePaper.pdf.
Ryabinin, K.V., Adaptive anti-aliasing for mobile devices, Vestn. Komp’yuternykh Inf. Tekhnol., 2014, no. 8, pp. 23–28.
Keval, H. and Sasse, M.A., To catch a thief–you need at least 8 frames per second: The impact of frame rates on user performance in a CCTV detection task, Proc.16th ACM Int. Conf. Multimedia, 2008, pp. 941–944.
Author information
Authors and Affiliations
Corresponding author
Additional information
Original Russian Text © K.V. Ryabinin, S.I. Chuprina, 2016, published in Programmirovanie, 2016, Vol. 42, No. 6.
Rights and permissions
About this article
Cite this article
Ryabinin, K.V., Chuprina, S.I. A unified approach to adapt scientific visualization systems to third-party solvers. Program Comput Soft 42, 347–355 (2016). https://doi.org/10.1134/S0361768816060049
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1134/S0361768816060049