[1]DING Ke,TAN Ying.A review on general purpose computing on GPUs and its applications in computational intelligence[J].CAAI Transactions on Intelligent Systems,2015,10(1):1-11.[doi:10.3969/j.issn.1673-4785.201403072]
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A review on general purpose computing on GPUs and its applications in computational intelligence

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 10 Number of periods: 2015 1 Page number: 1-11 Column: 综述 Public date: 2015-03-25
Title:
A review on general purpose computing on GPUs and its applications in computational intelligence
Author(s):
DING Ke1; 2;  TAN Ying1; 2
1. Key Laboratory of Machine Perception (MOE), Peking University, Beijing 100871, China;
2. School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China
Keywords:
computational intelligence; swarm intelligence; evolutionary algorithms; machine learning; deep learning; graphics processing unit (GPU); general purpose computing on GPUs; heterogonous computing; high performance computing (HPC)
CLC:
TP301
DOI:
10.3969/j.issn.1673-4785.201403072
Abstract:
The GPU enjoys the characteristics of high parallelism, low energy consumption and cheap price. Compared with the traditional CPU platform, it is especially suitable for tasks with high data parallelism. GPU computing has come into the mainstream of high performance computation (HPC) due to the emerging of development platforms like CUDA and OpenCL. The GPU’s enormous computational power greatly promotes computational intelligence. A great success has been achieved in the fields such as deep learning and swarm intelligence optimization, and several breakthroughs have been seen in image, and speech recognition because of GPU. Though suffering some drawbacks, GPUs provide common people and small institutions with enormous computing power. This has changed the set-up of scientific computing and programming model because it could only be provided by expensive supercomputers. To help researchers in the field of computational intelligence better utilize GPUs, a detailed survey of GPGPU is given in this paper。First, the characteristics and advantages of GPUs against CPUs are presented. Then we briefly review the development of GPU hardware followed by a survey of the evolution of development tools for GPGPU; special attention is drawn to two major platforms, CUDA and OpenCL. We end this paper with our perspectives of the challenges and trends of GPGPU. We point out that embedding and cluster are two major trends for GPGPU and as both academia and industry continue to see increasing progress in artificial intelligence, the GPU will be more widely used in more domains.
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