TY - GEN
T1 - Distributed particle-based rendering framework for large data visualization on hpc environments
AU - Nonaka, Jorji
AU - Sakamoto, Naohisa
AU - Shimizu, Takashi
AU - Fujita, Masahiro
AU - Ono, Kenji
AU - Koyamada, Koji
N1 - Funding Information:
Some of the results were obtained by using the K computer at RIKEN AICS (Advanced Institute for Computational Science) in Kobe, Japan. This work has been partially supported by JSPS under KAKENHI (Grant-in-Aid for Scientific Research) Number 26280043.
PY - 2017/9/12
Y1 - 2017/9/12
N2 - In this paper, we present a distributed data visualization framework for HPC environments based on the PBVR (Particle Based Volume Rendering) method. The PBVR method is a kind of point-based rendering approach where the volumetric data to be visualized is represented as a set of small and opaque particles. This method has the object-space and image-space variants, defined by the place (object or image- space) where the particle data sets are generated. We focused on the object-space approach, which has the advantage when handling large-scale simulation data sets such as those generated by modern HPC systems. In the object-space approach, the particle generation and the subsequent rendering processes can be easily decoupled. In this work, we took advantage of this separability to implement the proposed distributed rendering framework. The particle generation process utilizes the functionalities provided by the KVS (Kyoto Visualization System), and the particle rendering process utilizes the functionalities provided by the HIVE (Heterogeneously Integrated Visual- analytics Environment). The proposed distributed visualization framework is targeted to work also on systems without any hardware graphics acceleration capability, which are commonly found on modern HPC operational environments. We evaluated this PBVR-based distributed visualization infrastructure on the K computer operational environment by utilizing a CPU-only processing server for the particle data generation and rendering. In this preliminary evaluation, using some CFD (Computational Fluid Dynamics) simulation data sets, we obtained encouraging results for pushing further the development in order to make this system available as an effective visualization alternative for the HPC users.
AB - In this paper, we present a distributed data visualization framework for HPC environments based on the PBVR (Particle Based Volume Rendering) method. The PBVR method is a kind of point-based rendering approach where the volumetric data to be visualized is represented as a set of small and opaque particles. This method has the object-space and image-space variants, defined by the place (object or image- space) where the particle data sets are generated. We focused on the object-space approach, which has the advantage when handling large-scale simulation data sets such as those generated by modern HPC systems. In the object-space approach, the particle generation and the subsequent rendering processes can be easily decoupled. In this work, we took advantage of this separability to implement the proposed distributed rendering framework. The particle generation process utilizes the functionalities provided by the KVS (Kyoto Visualization System), and the particle rendering process utilizes the functionalities provided by the HIVE (Heterogeneously Integrated Visual- analytics Environment). The proposed distributed visualization framework is targeted to work also on systems without any hardware graphics acceleration capability, which are commonly found on modern HPC operational environments. We evaluated this PBVR-based distributed visualization infrastructure on the K computer operational environment by utilizing a CPU-only processing server for the particle data generation and rendering. In this preliminary evaluation, using some CFD (Computational Fluid Dynamics) simulation data sets, we obtained encouraging results for pushing further the development in order to make this system available as an effective visualization alternative for the HPC users.
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U2 - 10.1109/HPCS.2017.54
DO - 10.1109/HPCS.2017.54
M3 - Conference contribution
AN - SCOPUS:85032357082
T3 - Proceedings - 2017 International Conference on High Performance Computing and Simulation, HPCS 2017
SP - 300
EP - 307
BT - Proceedings - 2017 International Conference on High Performance Computing and Simulation, HPCS 2017
A2 - Smari, Waleed W.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th International Conference on High Performance Computing and Simulation, HPCS 2017
Y2 - 17 July 2017 through 21 July 2017
ER -