文章基本信息

标题：A Survey of Spiking Neural Networks and Support Vector Machine Performance Byusinggpu's
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作者：Israel Tabarez-Paz ; Neil Hernandez-Gress ; Miguel Gonzalez Mendoza 等
期刊名称：International Journal on Soft Computing
电子版ISSN：2229-7103
出版年度：2013
卷号：4
期号：3
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：In this paper we study theperformance of Spiking Neural Networks (SNN)and Support Vector Machine(SVM) by using a GPU, model GeForce 6400M. Respect to applications of SNN, the methodology may beused for clustering, classification of databases, odor, speech and image recognition..In case ofmethodology SVM, is typically applied for clustering, regression and progression. According to particularcharacteristicsof these methodologies,theycan be parallelizedin several grades.However, level ofparallelism is limited to architecture of hardware. So, is very sure to get better results using otherhardware with more computational resources.The different approaches are evaluated by the trainingspeed and performance. On the other hand,some authors have coded algorithms SVM light, but nobodyhas programming QP SVM in a GPU. Algorithms were coded by authors in the hardware, like Nvidia card,FPGA or sequential circuits that depends on methodology used, to compare learning timewith betweenGPU and CPU. Also, in the survey we introduce a brief description of the types of ANN and its techniquesof execution to be related with results of researching.
关键词：GPU;Spiking Neural Networks; Support Vector Machines; pattern recognition