Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate

被引：0

作者：

Billaudelle, S. ^{[1
]}

Stradmann, Y. ^{[1
]}

Schreiber, K. ^{[1
]}

Cramer, B. ^{[1
]}

Baumbach, A. ^{[1
]}

Dold, D. ^{[1
]}

Goeltz, J. ^{[1
]}

Kungl, A. F. ^{[1
,3
,4
]}

Wunderlich, T. C. ^{[1
]}

Hartel, A. ^{[1
]}

Mueller, E. ^{[1
]}

Breitwieser, O. ^{[1
]}

Mauch, C. ^{[1
]}

Kleider, M. ^{[1
]}

Gruebl, A. ^{[1
]}

Stoeckel, D. ^{[1
]}

Pehle, C. ^{[1
]}

Heimbrecht, A. ^{[1
]}

Spilger, P. ^{[1
]}

Kiene, G. ^{[1
]}

Karasenko, V ^{[1
]}

Senn, W. ^{[2
]}

Petrovici, M. A. ^{[1
,2
]}

Schemmel, J. ^{[1
]}

Meier, K. ^{[1
]}

机构：

[1] Heidelberg Univ, Kirchhoff Inst Phys, Heidelberg, Germany

[2] Univ Bern, Dept Physiol, Bern, Switzerland

[3] Berlin Inst Hlth, Berlin, Germany

[4] Charite, Berlin, Germany

来源：

2020 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS) | 2020年

关键词：

MEMORY;

D O I：

10.48350/149640

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 first experimental results on the novel BrainScaleS-2 neuromorphic architecture based on an analog neuro-synaptic core and augmented by embedded microprocessors for complex plasticity and experiment control. The high acceleration factor of 1000 compared to biological dynamics enables the execution of computationally expensive tasks, by allowing the fast emulation of long-duration experiments or rapid iteration over many consecutive trials. The flexibility of our architecture is demonstrated in a suite of five distinct experiments, which emphasize different aspects of the BrainScaleS-2 system.

引用

页数：5

共 50 条

[1] Live Demonstration: Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate
Billaudelle, S.
Stradmann, Y.
Schreiber, K.
Cramer, B.
Baumbach, A.
Dold, D.
Goeltz, J.
Kungl, A. F.
Wunderlich, T. C.
Hartel, A.
Mueller, E.
Breitwieser, O.
Mauch, C.
Kleider, M.
Gruebl, A.
Stoeckel, D.
Pehle, C.
Heimbrecht, A.
Spilger, P.
Kiene, G.
Karasenko, V
Senn, W.
Petrovici, M. A.
Schemmel, J.
Meier, K.
[J]. 2020 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2020,
[2] Accelerated Physical Emulation of Bayesian Inference in Spiking Neural Networks
Kungl, Akos F.
Schmitt, Sebastian
Klaehn, Johann
Mueller, Paul
Baumbach, Andreas
Dold, Dominik
Kugele, Alexander
Mueller, Eric
Koke, Christoph
Kleider, Mitja
Mauch, Christian
Breitwieser, Oliver
Leng, Luziwei
Guertler, Nico
Guettler, Maurice
Husmann, Dan
Husmann, Kai
Hartel, Andreas
Karasenko, Vitali
Gruebl, Andreas
Schemmel, Johannes
Meier, Karlheinz
Petrovici, Mihai A.
[J]. FRONTIERS IN NEUROSCIENCE, 2019, 13
[3] Compiling Spiking Neural Networks to Neuromorphic Hardware
Song, Shihao
Balaji, Adarsha
Das, Anup
Kandasamy, Nagarajan
Shackleford, James
[J]. 21ST ACM SIGPLAN/SIGBED CONFERENCE ON LANGUAGES, COMPILERS, AND TOOLS FOR EMBEDDED SYSTEMS (LCTES '20), 2020, : 38 - 50
[4] Mapping Spiking Neural Networks to Neuromorphic Hardware
Balaji, Adarsha
Das, Anup
Wu, Yuefeng
Huynh, Khanh
Dell'Anna, Francesco G.
Indiveri, Giacomo
Krichmar, Jeffrey L.
Dutt, Nikil D.
Schaafsma, Siebren
Catthoor, Francky
[J]. IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS, 2020, 28 (01) : 76 - 86
[5] Neuromorphic Architectures for Spiking Deep Neural Networks
Indiveri, Giacomo
Corradi, Federico
Qiao, Ning
[J]. 2015 IEEE INTERNATIONAL ELECTRON DEVICES MEETING (IEDM), 2015,
[6] A Survey of Neuromorphic Computing Based on Spiking Neural Networks
ZHANG Ming
GU Zonghua
PAN Gang
[J]. Chinese Journal of Electronics, 2018, 27 (04) : 667 - 674
[7] Neuromorphic Sentiment Analysis Using Spiking Neural Networks
Chunduri, Raghavendra K.
Perera, Darshika G.
[J]. SENSORS, 2023, 23 (18)
[8] Neuromorphic deep spiking neural networks for seizure detection
Yang, Yikai
Eshraghian, Jason K.
Truong, Nhan Duy
Nikpour, Armin
Kavehei, Omid
[J]. NEUROMORPHIC COMPUTING AND ENGINEERING, 2023, 3 (01):
[9] Tutorial: Neuromorphic spiking neural networks for temporal learning
Jeong, Doo Seok
[J]. JOURNAL OF APPLIED PHYSICS, 2018, 124 (15)
[10] Neuromorphic Data Augmentation for Training Spiking Neural Networks
Li, Yuhang
Kim, Youngeun
Park, Hyoungseob
Geller, Tamar
Panda, Priyadarshini
[J]. COMPUTER VISION, ECCV 2022, PT VII, 2022, 13667 : 631 - 649

← 1 2 3 4 5 →