Analysis of GPU Parallel Computing based on Matlab
Mingzhe Wang, Bo Wang, Qiu He, Xiuxiu Liu, Kunshuai Zhu
TL;DR
This paper investigates GPU-based parallel computing in Matlab, demonstrating that GPUs significantly accelerate parallel operations but may be slower for logical instructions compared to CPUs.
Contribution
It provides an analysis of GPU working principles and experimental results comparing Matlab GPU and CPU performance for different types of computations.
Findings
GPU computing is faster than CPU for parallel operations
GPU is slower than CPU for logical instructions
Experimental analysis supports GPU acceleration benefits in Matlab
Abstract
Matlab is very widely used in scientific computing, but Matlab computational efficiency is lower than C language program. In order to improve the computing speed, some toolbox can use GPU to accelerate the computation. This paper describes GPU working principle, our experiments and results analysis of parallel computing by using GPU based on Matlab. Experimental results show that for parallel operations, GPU computing speed is faster than CPU, for the logical instructions, GPU computing speed is slower than CPU.
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Taxonomy
TopicsParallel Computing and Optimization Techniques · Embedded Systems and FPGA Design · Advanced Technology in Applications