This document discusses using CUDA technology to perform wave simulations. The goal is to investigate the processing speeds of the GPU and CPU for wave simulation. The method uses CUDA APIs to allocate device memory and copy data between the host and device. Wave simulations are performed by both the GPU and CPU, and processing times are measured to compare performance. Results found that the GPU's processing speed was considerably higher than the CPU's, especially for larger numbers of particles.

1. Wave simulation using CUDA
s1170143 Ryo Kawamukai
Computer Graphics laboratory
University of AIZU
Supervised by Prof.Gennadiy Nikishkov

2. Outline
● Introduction
-Background
-Purpose
● Methd
-CUDA technology
-Wave Simulation
● Summary
● Future Work

3. Introduction -Background
In recent years, the processing speed of current graphics hardware
is equal to the ten years ago super computer.
A Graphics Processing Unit (GPU) is a dedicated graphics
rendering hardware.
The processing speed of the GPU is higher than that of the CPU.
Now, the GPU is used for general purpose computations not only
for graphics rendering.

4. Introduction -Purpose
The purpose of this research is:
Perform wave simulation using CUDA technology.
Investigate processing speed of the GPU and CPU, and
find the situations when the GPU processing speed
considerably exceeds CPU speed in wave simulation.
If I could, I make computing speed of the simulation
faster.

5. Method -CUDA technology
Device Memory f_d Host Code Host Memory f_h
//Memory Pointer
float f_d,f_h;
CUDA API
cudaMalloc(&f_d);
cudaMemcpy(f_h,f_d);
Device Code //Kernel function
__global__ func<<<Dg,Db>>>(f_d);
func(f_d){ }

6. Method -Wave Simulation
Result of wave simulation are rendered by OpenGL as
a real time 3D visualization.
This simulation are performed by the GPU and the
CPU.
Processing speed is measured to compare
performance.

7. Summary
In this research, wave simulation is performed using CUDA
technology.
Processing time for computation and total time of particle
simulation using the GPU and the CPU is measured.
Comparison shows that processing speed of the GPU is
considerably higher than processing speed of the CPU.
Larger number of particles leads to more efficient
simulation on the GPU in comparison to the CPU.

8. Future Work
To give proving data that it became early.
If I could, I make computing speed of the
simulation faster.