Another Parallelism Technique of GLCM Implementation Using CUDA Programming

Two-dimensional (2-D) ice flow thermodynamics coupled model acts as a vital role for visualizing the ice sheet behaviours of the Antarctica region and the climate system. One of the parameters used in this model is ice thickness. Explicit method of finite difference method (FDM) is used to discretize the ice thickness equation. After that, the equation will be performed on Compute Unified Device Architecture (CUDA) programming by using Graphics Processing Unit (GPU) platform. Nowadays, the demand of GPU for solving the computational problem has been increasing due to the low price and high performance computation properties. This paper investigates the performance of GPU hardware supported by the CUDA parallel programming and capable to compute a large sparse complex system of the ice thickness equation of 2D ice flow thermodynamics model using multiple cores simultaneously and efficiently. The parallel performance evaluation (PPE) is evaluated in terms of execution time, speedup, efficiency, effectiveness and temporal performance.

Download Full-text

Research on the single-host parallel computing with the local time step scheme for modeling of hydro-sediment-morphodynamic processes

10.5194/egusphere-egu21-7027 ◽

2021 ◽

Author(s):

Zixiong Zhao ◽

Peng Hu ◽

Wei Li ◽

Zhixian Cao ◽

Zhiguo He

Keyword(s):

Parallel Computing ◽

Local Time ◽

High Performance ◽

Water Model ◽

Time Step ◽

Time Stepping ◽

Computational Performance ◽

Cuda Programming ◽

Single Host ◽

Algorithmic Acceleration

<p>In recent decades, computational hydraulics and sediment modelling have a great development due to compute technology. Applying a finite-volume Godunov-type hydrodynamic shallow water model with hydro-sediment-morphodynamic processes, this work demonstrates and analysis the ability of single-host parallel computing technology with algorithmic acceleration technology. This model is implemented for high-performance computing using the NVIDIA&#8217;s Compute Unified Device Architecture (CUDA) programming framework, using a domain decomposition technique and across multiple cores through an efficient implementation of the Open Multi-Processing (Open MP) architecture, and using an algorithmic acceleration technology named local time stepping scheme (LTS), which is capable of obtain much efficiency improvement via different time step sizes for different grid sizes. The model is applied for three cases, through which we compare the effectiveness of CPU, Open MP, Open MP+LTS, CUDA, and CUDA+LTS, demonstrating high computational performance across CUDA+LTS which can lead to speedups of 40 times with respect to CPU and high-precision results across CUDA +LTS.</p><p>KEY WORDS: Hydro-sediment-morphological modeling; local time step; Open MP; CUDA.</p>

Download Full-text