High performant simulations of cerebellar Golgi cells activity

被引:8
作者
Florimbi, Giordana [1 ]
Torti, Emanuele [1 ]
Danese, Giovanni [1 ]
Leporati, Francesco [1 ]
机构
[1] Univ Pavia, Dept Elect Comp & Biomed Engn, Pavia, Italy
来源
2017 25TH EUROMICRO INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED AND NETWORK-BASED PROCESSING (PDP 2017) | 2017年
关键词
Cerebellar neuron simulation; Parallel simulations; GPU; Multicore CPU; Computational modeling; Biological system modeling; MODEL; PACEMAKING; FREQUENCY;
D O I
10.1109/PDP.2017.91
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The use of High Performance Computing (HPC) technologies is gaining interest in the field of neuronal activity simulations. In fact, scientists' main goal is to understand and reproduce cells behavior in a realistic way. This will allow undertaking in silico experiments, instead of in vivo ones, to test new medicines, to study cerebral pathologies and to discover innovative therapies. To this aim, two main requirements are necessary: neurons have to be described by realistic models and their simulation hopefully have to satisfy the real-time constraint. This last property is very hard to accommodate because models used in these works are very heavy from the computational point of view. For this reason, authors decide to exploit Graphic Processing Unit (GPU) technology to simulate the cellular activity of Golgi cells, which constitute the cerebellar cortex. This paper describes an efficient Golgi cell activity simulation performed using NVIDIA GPUs. Results show that simulation times are reduced from 41 hours to about 2 hours when simulating 400'000 different cells.
引用
收藏
页码:527 / 534
页数:8
相关论文
共 22 条
[1]   A review of the integrate-and-fire neuron model: I. Homogeneous synaptic input [J].
Burkitt, A. N. .
BIOLOGICAL CYBERNETICS, 2006, 95 (01) :1-19
[2]   The cerebellar Golgi cell and spatiotemporal organization of granular layer activity [J].
D'Angelo, Egidio ;
Solinas, Sergio ;
Mapelli, Jonathan ;
Gandolfi, Daniela ;
Mapelli, Lisa ;
Prestori, Francesca .
FRONTIERS IN NEURAL CIRCUITS, 2013, 7
[3]  
deCamargo R. Y., 2011, 18 INT C HIGH PERF C, P1, DOI [10.1109/HiPC.2011.6152427, DOI 10.1109/HIPC.2011.6152427]
[4]   The Human Brain Project: Parallel technologies for biologically accurate simulation of Granule cells [J].
Florimbi, Giordana ;
Torti, Emanuele ;
Masoli, Stefano ;
D'Angelo, Egidio ;
Danese, Giovanni ;
Leporati, Francesco .
MICROPROCESSORS AND MICROSYSTEMS, 2016, 47 :303-313
[5]  
Guoli Ji, 2012, 2012 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES 2012), P231, DOI 10.1109/IECBES.2012.6498184
[6]   A QUANTITATIVE DESCRIPTION OF MEMBRANE CURRENT AND ITS APPLICATION TO CONDUCTION AND EXCITATION IN NERVE [J].
HODGKIN, AL ;
HUXLEY, AF .
JOURNAL OF PHYSIOLOGY-LONDON, 1952, 117 (04) :500-544
[7]   Which model to use for cortical spiking neurons? [J].
Izhikevich, EM .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2004, 15 (05) :1063-1070
[8]   Simple model of spiking neurons [J].
Izhikevich, EM .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2003, 14 (06) :1569-1572
[9]  
Jalife A. A., 2012, WCCI IEEE WORLD C CO, P1
[10]   Using a million cell simulation of the cerebellum: Network scaling and task generality [J].
Li, Wen-Ke ;
Hausknecht, Matthew J. ;
Stone, Peter ;
Mauk, Michael D. .
NEURAL NETWORKS, 2013, 47 :95-102