Abstract
This paper presents a GPU-based parallelized and a CPU-based serial Monte-Carlo method for breakage of a particle. We compare the efficiency of the graphic card’s graphics processing unit (GPU) and the general-purpose central processing unit (CPU), in a simulation using Monte Carlo (MC) methods for processing the particle breakage. Three applications are used to compare the computational performance times, clock cycles and speedup factors, to find which platform is faster under which conditions. The architecture of the GPU is becoming increasingly programmable; it represents a potential speedup for many applications compared to the modern CPU. The objective of the paper is to compare the performance of the GPU and Intel Core i7-4790 multicore CPU. The implementation for the CPU was written in the C programming language, and the GPU implemented the kernel using Nvidia’s CUDA (Compute Unified Device Architecture). This paper compares the computational times, clock cycles and the speedup factor for a GPU and a CPU, with various simulation settings such as the number of simulation entries (SEs), for a better understanding of the GPU and CPU computational efficiency. It has been found that the number of SEs directly affects the speedup factor.
Highlights
The breakage of particles is of interest in various fields of engineering and scientific research, including chemical engineering, aerosols, agriculture and medicine [1,2,3]
The CPU invokes the task on the graphics processing unit (GPU), and the execution of the kernel is handled by the CUDA library, which runs on the central processing unit, while the GPU executes the kernel
We provided here a new background for modelling particle breakage using a graphics processing unit as a parallel environment and a CPU for serial processing
Summary
The breakage of particles is of interest in various fields of engineering and scientific research, including chemical engineering, aerosols, agriculture and medicine [1,2,3]. The time-driven Monte Carlo (MC) approach has been implemented for solving the PBE for breakage on the CPU [3, 6] which uses serial processing, and on the GPU [1, 3], which facilitates parallel processing. (2) The differences between the GPU and CPU computational times and the speedup factor for a given breakage rate and breakage function The importance of this reported investigation is to provide awareness about parallel processing can save time and cost.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
