Real-time Simulation Of Fireworks Based On CUDA Platform And Particle System Technology

In the field of Computer Graphics, firework is one reproduction of the realworld that people have been trying to use computer. Fireworks play an importantpart in people’s festival celebrating, which appeared in China as early as thespring and autumn Period. It is difficult to use a conventional computer graphicsmodeling methods to simulate fireworks scene, because it has an abundantsurface texture and an irregular outer contour, changes dynamically andrandomly with time. The key issues that need to be addressed are how to modelthe fireworks scene simplify and effective.Particle system technology can achieve the dynamic and randomness of thefireworks scene, so it’s one of the most effective methods of analog boundaryfuzzy scene, whose advantages is using simple fireworks particles to construct acomplex scene, and have strong element of truth and the real-time nature.However it is difficult for traditional computer graphics. To get the image of thetrue level of real-time rendering, we need to use a large number of particles in asimulation scenario, whose demands are high on computer hardware. CUDAplatform used in fireworks simulation based on particle system technology isbecause CUDA platform can take full advantage of the parallel computingpower of the GPU, put fireworks particle attributes updated calculation on theGPU to improve the speed of the attribute update effectively. Using CUDA andOpenGL interoperability functions to reduce the communication between theCPU and the GPU, the concrete realization of the process by the CPU isinitialized particle attribute data transferred to the GPU, and sent directly to thegraphics driver updated in parallel by CUDA platform kernel functionprocedures for rendering without the need to return the CPU. Also in accordancewith the procedures in operational characteristics of the data, the paper combined with the CUDA memory model program data stored in the graphicsmemory using CUDA function to improve the efficiency of code execution.Taken optimization strategy by optimizing memory access, the instructionstream, to minimize the exchange of data between the redundant execution ofthe instruction and a memory and improve the efficiency of the implementationof the code. The experiments shows that based the CUDA platform fireworksanalog to real-time requirements, and the simulation results significantly betterthan the CPU platform, when the particles are more.