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Journal Articles

VR extension of client server type particle-based volume visualization application

Kawamura, Takuma; Sakamoto, Naohisa*; Osaki, Tsukasa*

Journal of Advanced Simulation in Science and Engineering (Internet), 10(1), p.31 - 39, 2023/02

Visualization of large fluid computation results at remote locations by VR, especially using volume rendering, is one of the key challenges in the visualization field. The remote visualization application CS-PBVR is capable of interactive volume rendering of large-scale data in remote locations. In this study, the image generation of CS-PBVR was extended for head-mounted displays to develop a remote VR visualization application, VR-PBVR. We also developed a function that allows manipulation of visualization data by gesture control with both hands in VR space. We applied VR-PBVR to remote volume data and confirmed that it can visualize the data at interactive frame rates.

Journal Articles

Development of VR support and gesture control functions for particle-based visualization applications

Kawamura, Takuma; Sakamoto, Naohisa*

Dai-36-Kai Suchi Ryutai Rikigaku Shimpojiumu Koen Rombunshu (Internet), 3 Pages, 2022/12

Volume rendering is useful for visualizing computer fluid dynamics (CFD) data, and its VR visualization helps to understand complex 3D data. Volume rendering of large scale data in remote locations in VR space is an important issue of the visualization field. A remote visualization application CS-PBVR can interactively visualize the large-scale datasets in remote locations with volume rendering. In order to extend CS-PBVR into VR-PBVR which is applicable to a head mount display (HMD) Oculus rift S, we added a stereo image generation function, a gesture control function, and a renewed processing flow. VR-PBVR achieved interactive visualization of remotely located test dataset (2M cells) with 90 fps.

Journal Articles

Interactive in-situ steering and visualization of GPU-accelerated simulations using particle-based volume rendering

Kawamura, Takuma; Hasegawa, Yuta; Idomura, Yasuhiro

Proceedings of Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo 2020 (SNA + MC 2020), p.187 - 192, 2020/10

In order to realize the atmospheric dispersion prediction of pollutants, a fluid simulation by adaptive mesh refinement (AMR) optimized for GPU supercomputer has been developed, and interactive visualization and parameter steering of the simulation results are needed. In this study, we extend particle-based in-situ visualization method for structured grids into AMR, and enables in-situ steering of the simulation parameters by utilizing an in-situ control mechanism via files. By combining the developed method with plume dispersion simulation in urban areas running on a GPU platform, it was shown that human-in-the-loop pollution source search is possible without enormous parameter scanning.

Journal Articles

Performance evaluation of runtime data exploration framework based on in-situ particle based volume rendering

Kawamura, Takuma; Noda, Tomoyuki; Idomura, Yasuhiro

Supercomputing Frontiers and Innovations, 4(3), p.43 - 54, 2017/07

AA2017-0206.pdf:3.74MB

We examine the performance of the in-situ data exploration framework based on the in-situ Particle Based Volume Rendering (In-Situ PBVR) on the latest many-core platform. In-Situ PBVR converts extreme scale volume data into small rendering primitive particle data via parallel Monte-Carlo sampling without costly visibility ordering. This feature avoids severe bottlenecks such as limited memory size per node and significant performance gap between computation and inter-node communication. In addition, remote in-situ data exploration is enabled by asynchronous file-based control sequences, which transfer the small particle data to client PCs, generate view-independent volume rendering images on client PCs, and change visualization parameters at runtime. In-Situ PBVR shows excellent strong scaling with low memory usage up to about 100k cores on the Oakforest-PACS, which consists of 8,208 Intel Xeon Phi7250 (Knights Landing) processors.

Journal Articles

Open-source remote visualization software PBVR

Kawamura, Takuma

Keisan Kogaku Nabi, Nyusu Reta (Internet), 7, p.4 - 5, 2015/06

It has been difficult for traditional remote visualization systems to explore large-scale data because of bottlenecks such as visualization speed, memory limit, and data transfer time. Remote visualization software PBVR (Particle-Based Volume Rendering) employed client-server system and achieved interactive data exploration by converting the large-scale data to small particle data which is transferred to the client machine. We developed PBVR system as open source code and contributed an article about PBVR system.

Journal Articles

Multivariate volume rendering using transfer function synthesizer implemented in remote visualization system PBVR

Kawamura, Takuma; Idomura, Yasuhiro; Miyamura, Hiroko; Takemiya, Hiroshi

Proceedings of SIGGRAPH Asia 2015 (SA 2015) (Internet), 4 Pages, 2015/00

In this paper, we propose a novel transfer function design technique for multivariate volume rendering. This technique generates a multidimensional transfer function by logical synthesis of variables and transfer functions. This technique enables analysts to extract correlation of variables and to combine multivariate surface and volume shapes. And this technique is implemented in Remote Visualization System PBVR optimized to several supercomputers. An experiment for the multi-phase fuel melting simulation result in the nuclear energy field shows the powerful ability of this technique enough by extracting complex behavior of molten materials.

Oral presentation

Interactive remote visualization of large-scale simulation using PBVR

Kawamura, Takuma

no journal, , 

I was invited from the Science Council of Japan for an invited lecture on In-Situ PBVR visualization technology. To develop visualization technology for future Exascale simulation, the following three problems are bottlenecks. (1) Increase of communication cost under high parallel environment. (2) Low interactivity due to offline visualization for batch processing. (3) Visualization of multivariate data. In order to solve these problems, I developed the following three technologies. (1) Parallel volume rendering with high scalability by PBVR. (2) Framework that enables interactive operation by file-based control via storage. (3) Multidimensional transfer function generation technique for multivariate data. Applying the proposed method to fuel melting simulation JUPITER about 100 million degrees of freedom, we demonstrated the high scalability of visualization processing, the interactive operation at batch processing execution, and the effectiveness of multivariate visualization function.

Oral presentation

Remote interactive in-situ visualization using particle data for volume visualization

Kawamura, Takuma

no journal, , 

I presented the research result of "Remote Interactive In-Situ Visualization using Particle Data for Volume Visualization" founded by Joint Usage/Research Center for Interdisciplinary Large-scale Information Infrastructures (JHPCN), 2017. With increasing simulation scale, the conventional visualization process involving data transfer to the pre-post node requires a huge amount of work time. To enable real-time visualization and analysis of large-scale simulation, an interactive In-Situ visualization system using particle data for visualization was constructed in this research and this system was ported to the latest GPGPU, XeonPhi, and FX100 environments. Using this system, we confirmed that interactive visualization of batch processing simulations is possible.

Oral presentation

SIMD optimization of in-situ PBVR

Kawamura, Takuma; Idomura, Yasuhiro

no journal, , 

In-Situ PBVR using Particle-Based Volume Rendering (PBVR) is a framework that enables interactive visualization of simulations on supercomputers, and synthesis of volume data and transfer function by user specified algebraic equation by means of computer algebra system. Simulations are accelerated by the appearance of many core architecture, and optimization of in-situ PBVR is also required. We constructed a novel computer algebra system using reverse Polish notation for SIMD optimization of In-Situ PBVR. We applied the proposed method to fuel melting simulation in the nuclear field, and visualization performance was improved by more than 10 times on the latest KNL architecture.

Oral presentation

SIMD optimization of in-situ visualization system using particle data for visualization

Kawamura, Takuma

no journal, , 

I present the research result of "Remote Interactive In-Situ Visualization using Particle Data for Volume Visualization" supported by the Joint Usage/Research Center for Interdisciplinary Large-scale Information Infrastructures (JHPCN), 2017. With the increase of simulation scale, the conventional visualization process involving data transfer to the pre-post node requires a huge processing cost. To enable real-time visualization and analysis of large-scale simulations, an interactive In-Situ visualization system using particle data for visualization is optimized for the latest SIMD platforms such as XeonPhi, and FX100. Using this system, interactive visualization at runtime is enabled for batch processing simulations.

Oral presentation

In-situ visualization based on particle based volume rendering

Kawamura, Takuma

no journal, , 

We discuss the development and application of an in-situ visualization system using particle based visualization data. As the simulation becomes larger, the conventional visualization method involving data transfer to the pre-post node requires a huge amount of processing time. In this study, in order to enable real-time visualization and analysis for large-scale simulations, an interactive in-situ visualization system using particle data was developed and optimized for the latest many-core environment. Using the developed system, it was confirmed that interactive visualization is possible when executing batch processing of simulations. A visualization example of AMR based simulations on the latest GPGPU machine is also reported.

Oral presentation

Interactive In-Situ Steering by File-base Control using Particle-based In-Situ Visualization Framework

Kawamura, Takuma; Hasegawa, Yuta

no journal, , 

In a large-scale simulation that uses a huge amount of computational resources and runs for a long time on a supercomputer, it is difficult to repeatedly perform recalculation due to adjustment of computational parameters. We have developed a technique for interactive manipulation of simulation parameters by file-based control on an in-situ visualization framework using particle-based volume rendering. We have confirmed that it can be applied to fluid simulation on GPU clusters for interactive visualization and parameter manipulation.

Oral presentation

VR for remote visualization applications for large particle-based data

Kawamura, Takuma; Sakamoto, Naohisa*

no journal, , 

Visualization of remote large-scale fluid data in VR space is an important issue in fluid data visualization. In this study, we developed VR-PBVR by extending CS-PBVR, a remote visualization application for large-scale data, for the Oculus rift S HMD. In this development, a highly operable gesture control was implemented for the coordinate transformation of visualization data in VR space. VR-PBVR was able to visualize remote test data at interactive frame rates.

Oral presentation

Image quality improvement of particle-based rendering using multi-kernel denoising autoencoder

Morii, Masahiro*; Sakamoto, Naohisa*; Kawamura, Takuma

no journal, , 

Particle-Based Volume Rendering (PBVR) efficiently visualizes simulation result data by converting it into compressed visualizable particles. It is utilized in applications for visualizing large-scale data from remote locations. The image quality of PBVR depends on the number of particles used for visualization, leading to an increase in the transmitted particle size when generating high-resolution images for remote visualization. This research proposed a multi-kernel denoising autoencoder tailored for PBVR, and confirmed its effectiveness using test data.

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