The purpose of this paper was to apply and express to a particle production system based on mathematical models to raise a cloud of spray. It was used that a crash was used to conflict expanding wave generation model and applying the block cover. Also, we applied to the KD-tree in order to reduce trial search. The block cover was created with the creation on the phase of height values. The waves and wind made by character's emotions, which input use as the value. Reached a certain level in both cases, waves and waves are generated a cloud of spray by the collision. The repetition of generated waver was applied with the Windows function. Handling conflict is affected in a cloud of spray. Generated KD-Tree renewal grid is beyond the range in block cover and is not a uniform height. It is built that the processing of collision is not performed by the level on height of a wave. This process was designed by the best statistical analysis after reviewing sufficient factual nature. This paper is applied with a cloud of splay for emotional online games like game that tried to apply the spray can apply for the environment. If you use a physically-based model requires a lot of calculation time, the physically-based models ask a lot of complicated calculation time for solver this program and high-performance systems. However, a block-cover can be role of a very effective way for enough performance. Through the analysis result can be obtained a sufficient result in easy implementation of the cloud of spray

This paper presents a parallel kd-tree traversal algorithm based on the parallel binary radix tree construction scheme proposed by Tero Karras in 2012. In his paper, Tero Karras proposed parallel tree construction algorithm which can maximize the utilization of GPU threads, but implementation and analysis of kd-tree are not fully discussed. This paper aims to fill the gap for the specific kd-tree cases. As an application for the kd-tree traversal method proposed in this paper, the proposed method has been implemented with NVIDIA’s CUDA framework and tested on NVIDIA’s realtime raytracing library, OptiX. As a result, the proposed method can construct tree structures within the requirement for realtime process, but still needs specialized spatial caching data structure like the “primitive tree” for highly detailed meshes to handle spatial queries as fast as to visualize implicit surfaces under OptiX framework. However, the proposed method can be applied to dynamic collision detection and manage scene and object information for game applications thanks to its fast tree construction process. Also, realtime raytracing can be applied to game applications based on this study.

The purpose of this study was to make the sea with rending of ocean by using the proper algorithm for an emotional online game. We used statistical model to make the sea in this study. In measuring the wave height, we used Fast Fourier Transformation (FFT) to calculate the sum of amplitude and phrase quickly with random numbers of the time. We eliminated the overlap functions of sine and cosines by using the repeatability of trigonometric function. We saved the values of trigonometric function in memory space. Therefore, we could deal with the repetitive calculations by memory access because the same values are repeated in the standard based on π within one cycle of 2π in sine and cosine functions. By changing the sampling size of Windows function, we calculated the mobility on each local area and we applied this mobility to this study according to hierarchical structure. In addition, we used the reflectivity differently by putting the value of k,r into the effect Fresnel reflection. The reason why we used this method was to make the sea look more realistic. In the aspect of the intensity of light of the sea, we did not calculate it and we applied KD- Tree data structure on the density of the values occurred at the time of the sea was created. The advantage of this method was to reduce search time effectively. In this Tree structure, index time  log  , search time and    log  time are spend, which is applied to the photon closed to  . In the case of KD-Tree, this is a very effective way in saving and recovering. One weakness was that we had to limit the effect of indirect illumination to express a wide sea. However, by using photon mapping, we solved this problem

GPU는 메모리 대역폭이 연산 속도를 결정하는 병목 지점이 된다. 즉, GPU 프로그래밍 시에는 불규칙적인 메모리 액세스나 다중 스레드들 사이에서의 서로 다른 명령 실행 분기가 발생하면 속도가 크게 저하되는 문제가 발생한다. 따라서 게임 엔진 충돌 처리용으로 사용되는 kd-tree와 같은 적응형 탐색(adaptive traverse) 기법은, 불규칙적인 메모리 액세스 및 서로 다른 명령 분기로 인해 지금까지 GPU 구조에 적합하지 않은 것으로 인식되어 왔다. 그러나 최근 NVIDIA의 Fermi 아키텍처의 등장과 함께 CPU에서처럼 GPU 다중 프로세서에도 캐시 메모리가 적용되고 있다. 본 논문에서는 이러한 새로운 GPU 아키텍처의 장점을 활용해서 충돌 처리 시간을 크게 줄일 수 있는 GPU 기반 kd-tree를 제안한다. 제안하는 GPU 기반 병렬 kd-tree는 체크 지점 65536 개에서 최근접 삼각형까지의 거리를 찾는 작업이 Fermi 아키텍처(캐시 적용) 기반에서 단일 코어 CPU 기반 kd-tree에 비해 평균 백 만 배 이상(1.0x106) 빨라졌으며, 이전 세대 Tesla 아키텍처(캐시 미적용) 기반 병렬 kd-tree에 비해서도 약 50 배 가까이 빠른 속도를 보였다.