Leaky integrate-and-fire model;
spike-response model;
template-scaling-based exponential function approximation;
spiking neural network;
FPGA IMPLEMENTATION;
DIGITAL HARDWARE;
NEURAL-NETWORKS;
SPIKING;
STDP;
BACKPROPAGATION;
D O I:
10.1109/TCSI.2020.3027583
中图分类号:
TM [电工技术];
TN [电子技术、通信技术];
学科分类号:
0808 ;
0809 ;
摘要:
We present a method to emulate a leaky integrate-and-fire (LIF) model in a field-programmable gate array (FPGA) in a hardware-efficient manner. The simplified spike-response model (SRM0) is chosen as an LIF model. For the hardware-efficient implementation of SRM0, we adopt the template-scaling-based exponential function approximation (TS-EFA). This method allows high precision and low latency exponential function approximations with the efficient use of hardware resources. We subsequently propose an algorithm for SRM0, which leverages the advantage of TS-EFA. An implementation of 512 neurons conforming to SRM0 in an FPGA highlights (i) high precision of SRM0 emulation (mean squared error of membrane potential approximation: 4 x 10(-12) - 1 x 10(-10)), (ii) low latency (eight clock cycles), and (iii) high efficiency in hardware usage (only 125b memory per neuron).ardware usage (only 125b memory per neuron).
机构:
CNRS, Lab Neurophys & Physiol, Unite Mixte Rech 8119, F-75270 Paris 06, France
Univ Paris 05, F-75270 Paris 06, France
NYU, Ctr Neural Sci, New York, NY 10003 USACNRS, Lab Neurophys & Physiol, Unite Mixte Rech 8119, F-75270 Paris 06, France
Graupner, Michael
Brunel, Nicolas
论文数: 0引用数: 0
h-index: 0
机构:
CNRS, Lab Neurophys & Physiol, Unite Mixte Rech 8119, F-75270 Paris 06, France
Univ Paris 05, F-75270 Paris 06, FranceCNRS, Lab Neurophys & Physiol, Unite Mixte Rech 8119, F-75270 Paris 06, France
机构:
CNRS, Lab Neurophys & Physiol, Unite Mixte Rech 8119, F-75270 Paris 06, France
Univ Paris 05, F-75270 Paris 06, France
NYU, Ctr Neural Sci, New York, NY 10003 USACNRS, Lab Neurophys & Physiol, Unite Mixte Rech 8119, F-75270 Paris 06, France
Graupner, Michael
Brunel, Nicolas
论文数: 0引用数: 0
h-index: 0
机构:
CNRS, Lab Neurophys & Physiol, Unite Mixte Rech 8119, F-75270 Paris 06, France
Univ Paris 05, F-75270 Paris 06, FranceCNRS, Lab Neurophys & Physiol, Unite Mixte Rech 8119, F-75270 Paris 06, France