Changes between Version 5 and Version 6 of UGT2011

Timestamp:

Nov 5, 2014 9:35:19 AM (10 years ago)

Author:

nakasato

Comment:

--

UGT2011

@@ -29 +29 @@
 = K.Seiwa =
 == GPU Acceleration of Numerical Simulation of Fluid by the Lattice Boltzmann Method ==
+   Numerical simulations of fluid are used for analyzing
+the gas and liquid motion of air or water. It has been developed
+drastically by the performance enhancement of the computers. It is
+regarded as important in the designing vehicle such as a car, an
+air plane, and a ship moving in the fluid.
+   The lattice Boltzmann method (LBM) is the one of the method for
+numerically simulating the thin fluid and it simulates the fluid
+field motion expressed by lattice and particles placed on the lattice
+points. When we need to analyze more strictly, we need many lattice
+and particles and this method will take longer time.
+   To simulate the fluid field effectively, I have implemented the LBM
+on Graphic Processing Unit (GPU). GPU is a processor turned for data
+parallel computation with a large number of computing cores. I try to
+accelerate the fluid simulation using OpenCL which is a framework for
+parallel programming. As the result, my numerical simulation by the
+LBM becomes faster about 5 times than on CPU. We conclude that using
+GPU is effective to accelerate the LBM simulations.
+
+
+file:///home/committee/aac/Thesis2011/s1150132
+
 
 = T.Suzuki =
 == OpenCL Implementation of Exact String Matching ==
+Graphics Processing Units (GPUs) have evolved over the past few years from dedicated graphics rendering devices to powerful parallel processors and they are outperforming traditional Central Processing Units (CPUs) in many areas of scientific computing. This paper presents experimental results on the parallel processing for some well known on-line string matching algorithms using OpenCL that is a standard API for writing parallel programs for CPU and GPU. I found that the simplest algorithm with help of vectorization is the fastest on GPU. The performance of my optimized string matching kernel on GPU is 10 times faster than the standard utility command “grep” for simultaneously matching enough large number of strings.
+
+
+file:///home/committee/aac/Thesis2011/s1160119
+
+
+
 
 = K.Nakamura =