journal article·2024-10-01Open access

Roadmap to neuromorphic computing with emerging technologies

Adnan Mehonic, Daniele Ielmini, Kaushik Roy, Onur Mutlu, Shahar Kvatinsky, Teresa Serrano-Gotarredona, Bernabe Linares-Barranco, Sabina Spiga, Sergey Savel’ev, Alexander G. Balanov, Nitin Chawla, Giuseppe Desoli, Gerardo Malavena, Christian Monzio Compagnoni, Zhongrui Wang, J. Joshua Yang, Syed Ghazi Sarwat, Abu Sebastian, Thomas Mikolajick, Stefan Slesazeck, Beatriz Noheda, Bernard Dieny, Tuo-Hung (Alex) Hou, Akhil Varri, Frank Brückerhoff-Plückelmann, Wolfram Pernice, Xixiang Zhang, Sebastian Pazos, Mario Lanza, Stefan Wiefels, Regina Dittmann, Wing H. Ng, Mark Buckwell, Horatio R. J. Cox, Daniel J. Mannion, Anthony J. Kenyon, Yingming Lu, Yuchao Yang, Damien Querlioz, Louis Hutin, Elisa Vianello, Sayeed Shafayet Chowdhury, Piergiulio Mannocci, Yimao Cai, Zhong Sun, Giacomo Pedretti, John Paul Strachan, Dmitri Strukov, Manuel Le Gallo, Stefano Ambrogio, Ilia Valov, Rainer Waser

APL Materials· Volume 12· Issue 10

Abstract

International audience
Only a short abstract or summary was supplied by the source.
Source: openalex_inverted_index · Quality: short

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Neural Networks and Reservoir Computing

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Electronic and Electrical Engineering, UCL 1 , Torrington Place, London WC1E 7JE,

Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano 2 , Piazza L. da Vinci 32, 20133 Milano,

School of Electrical and Computer Engineering, Purdue University 3 , West Lafayette, Indiana 47907,

Department of Information Technology and Electrical Engineering, ETH Zurich 4 , Gloriastrasse 35, 8092 Zurich,

Andrew and Erna Viterbi Faculty of Electrical and Computer Engineering, Technion–Israel Institute of Technology 5 , Haifa 3200003,

Instituto de Microelectrónica de Sevilla (IMSE-CNM), CSIC and University of Seville 6 , Avda. Américo Vespucio 28, 41092 Seville,

CNR-IMM Unit of Agrate Brianza 7 , Via C. Olivetti 2, 20864 Agrate Brianza (MB),

Department of Physics, Loughborough University 8 , Epinal Way, Loughborough LE11 3TU,

STMicroelectronics 9 , Knowledge Park III, Greater Noida 201304,

STMicroelectronics S.p.A., System Research and Application 10 , Via Tolomeo 1, 20010 Cornaredo (MI),

Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California 11 , Los Angeles, California 90089,

IBM Research Europe 12 , Säumerstrasse 4, 8803 Rüschlikon,

NaMLab gGmbH 13 , Nöthnitzer Stasse. 64a, 01187 Dresden,

Zernike Institute for Advanced Materials and CogniGron Center, University of Groningen 15 , Nijenborgh 4, 9747 AG Groningen,

CEA, CNRS, SPINTEC, Univ. Grenoble Alpes 16 , rue des Martyrs, 38000 Grenoble,

Institute of Electronics, National Yang Ming Chiao Tung University 17 , 1001 University Road, Hsinchu 30010,

Institute of Physics, University of Münster 18 , Heisenbergstraße 11, 48149 Münster,

Physical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST) 19 , Thuwal 23955-6900,

Department of Materials Science and Engineering, National University of Singapore 20 , Singapore 117575,

Peter Grünberg Institute 7, Forschungszentrum Jülich GmbH 21 , 52428 Jülich,

The Alan Turing Institute, British Library 22 , 96 Euston Road, London NW1 2DB,

School of Integrated Circuits, Peking University 23 , Beijing 100871,

CNRS, Centre de Nanosciences et de Nanotechnologies, Université Paris-Saclay 24 , 91120 Palaiseau,

CEA LETI, MINATEC Campus 25 , 17 rue des Martyrs, Grenoble 38054,

Institute for Artificial Intelligence and School of Integrated Circuits, Peking University 26 , No. 5 Yiheyuan Road, Haidian District, Beijing 100871,

References (100+)

Show source-provided references
1. Nature · 2022 · 604 · 25510.1038/s41586-021-04362-w ↗
2. Front. Neurosci. · 2016 · 10 · 33310.3389/fnins.2016.00333 ↗
3. IEEE J. Emerging Sel. Top. Circuits Syst. · 2018 · 8 · 8610.1109/jetcas.2018.2796379 ↗
4. IBM J. Res. Dev. · 2019 · 63 · 8:110.1147/JRD.2019.2934050 ↗
5. Nat. Electron. · 2020 · 3 · 43410.1038/s41928-020-0448-2 ↗
6. Front. Neurosci. · 2016 · 10 · 5710.3389/fnins.2016.00057 ↗
7. Nature · 2020 · 585 · 51810.1038/s41586-020-2735-5 ↗
8. APL Mach. Learn. · 2023 · 1 · 01090210.1063/5.0136403 ↗
9. Neuromorphic Comput. Eng. · 2022 · 2 · 02250110.1088/2634-4386/ac4a83 ↗
10. APL Mater. · 2021 · 9 · 05070210.1063/5.0047641 ↗
11. Proc. IEEE · 2023 · 112 · 54410.1109/JPROC.2024.3429360 ↗
12. iScience · 2020 · 23 · 10184610.1016/j.isci.2020.101846 ↗
13. Appl. Phys. Lett. · 2022 · 120 · 14040110.1063/5.0092382 ↗
14. Adv. Mater. · 2023 · 35 · 220509810.1002/adma.202205098 ↗
16. IEEE Spectrum · 1997 · 34 · 5210.1109/6.591665 ↗
17. Proc. IEEE · 1966 · 54 · 190110.1109/proc.1966.5273 ↗
18. IEEE J. Solid-State Circuits · 1974 · 9 · 25610.1109/jssc.1974.1050511 ↗
19. 2011
20. Proc. IEEE · 2012 · 100 · 195110.1109/jproc.2012.2190369 ↗
21. 2014
22. IEEE Des. Test · 2017 · 34 · 3910.1109/mdat.2016.2573586 ↗
23. ACM SIGPLAN Not. · 2018 · 53 · 31610.1145/3296957.3173177 ↗
24. 2021
25. 1994 · 24
26. 2022
27. 2007
28. 2014 · (full issue)10.14529/jsfi1401 ↗
29. Emerging Computing: From Devices to Systems · 2022 · 171
30. 2019
31. 2021
32. Nature · 2010 · 464 · 87310.1038/nature08940 ↗
33. IEEE Trans. Circuits Syst. · 2014 · 61 · 89510.1109/tcsii.2014.2357292 ↗
34. 2017
35. ACM SIGARCH Comput. Archit. News · 2016 · 44 · 1410.1145/3007787.3001139 ↗
36. 2021
37. Nature · 2015 · 521 · 6110.1038/nature14441 ↗
38. Proc. IEEE · 2014 · 102 · 147010.1109/jproc.2014.2346153 ↗
39. IEEE J. Solid-State Circuits · 2013 · 48 · 82710.1109/jssc.2012.2230553 ↗
40. IEEE J. Solid-State Circuits · 2008 · 43 · 56610.1109/jssc.2007.914337 ↗
41. 2017
42. 2020
43. 2005
44. Sensors · 2013 · 13 · 1421410.3390/s131014214 ↗
45. 2014
46. IEEE Trans. Pattern Anal. Mach. Intell. · 2013 · 35 · 270610.1109/tpami.2013.71 ↗
47. IEEE J. Solid-State Circuits · 2013 · 48 · 194310.1109/jssc.2013.2259038 ↗
48. Sci. Am. · 2012 · 306 · 5010.1038/scientificamerican0612-50 ↗
49. Towards biologically realistic multi-compartment neuron modelemulation in analog VLSI
50. Science · 2014 · 345 · 66810.1126/science.1254642 ↗
51. IEEE Micro · 2018 · 38 · 8210.1109/mm.2018.112130359 ↗
52. See https://www.intel.com/content/www/us/en/newsroom/news/intel-scales-neuromorphic-research-system-100-million-neurons.html for Intel report.
53. Nature · 2015 · 521 · 43610.1038/nature14539 ↗
54. Neural Networks · 2019 · 111 · 4710.1016/j.neunet.2018.12.002 ↗
55. IEEE J. Emerging Sel. Top. Circuits Syst. · 2022 · 12 · 89810.1109/jetcas.2022.3207514 ↗
56. Nature · 2022 · 608 · 50410.1038/s41586-022-04992-8 ↗
57. Nat. Electron. · 2018 · 1 · 10010.1038/s41928-018-0028-x ↗
58. J. Neural Eng. · 2016 · 13 · 05100110.1088/1741-2560/13/5/051001 ↗
59. J. Electron. Imaging · 2022 · 31 · 01090110.1117/1.jei.31.1.010901 ↗
60. Nat. Nanotechnol. · 2020 · 15 · 52910.1038/s41565-020-0655-z ↗
61. Neuromorphic Comput. Eng. · 2022 · 2 · 04200110.1088/2634-4386/ac9012 ↗
62. Adv. Phys.: X · 2016 · 2 · 8910.1080/23746149.2016.1259585 ↗
63. Nat. Nanotechnol. · 2020 · 15 · 51710.1038/s41565-020-0647-z ↗
64. Nat. Rev. Mater. · 2020 · 5 · 17310.1038/s41578-019-0159-3 ↗
65. Nat. Electron. · 2020 · 3 · 36010.1038/s41928-019-0360-9 ↗
66. Nat. Mater. · 2021 · 21 · 19510.1038/s41563-021-01099-9 ↗
67. Adv. Phys.: X · 2017 · 2 · 8910.1080/23746149.2016.1259585 ↗
68. Neuromorphic Comput. Eng. · 2022 · 2 · 01200210.1088/2634-4386/ac4918 ↗
69. Adv. Mater. · 2022 · 35 · 220477110.1002/adma.202204771 ↗
70. Nat. Electron. · 2018 · 1 · 38610.1038/s41928-018-0103-3 ↗
71. Adv. Intell. Syst. · 2020 · 2 · 200005510.1002/aisy.202000055 ↗
72. Nature · 2023 · 618 · 5710.1038/s41586-023-05973-1 ↗
73. Nat. Photonics · 2021 · 15 · 10210.1038/s41566-020-00754-y ↗
74. MRS Bull. · 2022 · 47 · 50210.1557/s43577-022-00358-7 ↗
75. Nature · 2022 · 601 · 21110.1038/s41586-021-04196-6 ↗
76. Nat. Commun. · 2022 · 13 · 579310.1038/s41467-022-33476-6 ↗
77. Nat. Commun. · 2022 · 13 · 350610.1038/s41467-022-31157-y ↗
78. Nanotechnology · 2018 · 30 · 01510210.1088/1361-6528/aae81c ↗
79. 2021
80. Nature · 2022 · 601 · 54910.1038/s41586-021-04223-6 ↗
81. Neural Networks · 2019 · 115 · 10010.1016/j.neunet.2019.03.005 ↗
82. Adv. Quantum Technol. · 2021 · 4 · 210005310.1002/qute.202100053 ↗
83. Appl. Phys. Rev. · 2020 · 7 · 01130210.1063/1.5120412 ↗
84. Brain Sci. · 2022 · 12 · 86310.3390/brainsci12070863 ↗
85. Appl. Phys. Rev. · 2020 · 7 · 01131210.1063/1.5118217 ↗
86. Nanotechnology · 2019 · 31 · 09200110.1088/1361-6528/ab554b ↗
87. Adv. Electron. Mater. · 2022 · 8 · 210112710.1002/aelm.202101127 ↗
88. Nat. Mater. · 2012 · 12 · 11410.1038/nmat3510 ↗
89. Nat. Mater. · 2016 · 16 · 10110.1038/nmat4756 ↗
90. Nat. Commun. · 2017 · 8 · 88210.1038/s41467-017-00869-x ↗
91. Chaos, Solitons Fractals · 2021 · 145 · 11080310.1016/j.chaos.2021.110803 ↗
92. Nat. Electron. · 2018 · 1 · 13710.1038/s41928-018-0023-2 ↗
93. Adv. Intell. Syst. · 2020 · 2 · 200008510.1002/aisy.202000085 ↗
94. Appl. Phys. Lett. · 2022 · 121 · 01050110.1063/5.0093964 ↗
95. Chaos, Solitons Fractals · 2021 · 149 · 11099710.1016/j.chaos.2021.110997 ↗
96. Chaos, Solitons Fractals · 2021 · 142 · 11038310.1016/j.chaos.2020.110383 ↗
97. Curr. Opin. Neurobiol. · 2014 · 25 · 15610.1016/j.conb.2014.01.008 ↗
98. Sci. Adv. · 2022 · 8 · eabl586510.1126/sciadv.abl5865 ↗
99. J. D. Monaco , K.Rajan, and G. M.Hwang, arXiv:2105.07284 (2021).
100. Nat. Rev. Mater. · 2022 · 7 · 57510.1038/s41578-022-00434-z ↗