人工智能加速器 (Chinese Wikipedia)

Analysis of information sources in references of the Wikipedia article "人工智能加速器" in Chinese language version.

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amazon.science

How silicon innovation became the 'secret sauce' behind AWS's success. Amazon Science. 2022年7月27日 [2024年7月19日]. （原始内容存档于2025年1月16日）.

amd.com

AMD XDNA Architecture.

apple.com

machinelearning.apple.com

Deploying Transformers on the Apple Neural Engine. Apple Machine Learning Research. [2023-08-24] （美国英语）.

archive.org

Dvorak, J.C. Inside Track. PC Magazine. 1990年5月29日 [2023年12月26日].

arxiv.org

Jouppi, Norman P.; et al. In-Datacenter Performance Analysis of a Tensor Processing Unit. ACM SIGARCH Computer Architecture News. 2017-06-24, 45 (2): 1–12. arXiv:1704.04760 . doi:10.1145/3140659.3080246  （英语）.
De Fabritiis, G. Performance of Cell processor for biomolecular simulations. Computer Physics Communications. 2007, 176 (11–12): 660–664. Bibcode:2007CoPhC.176..660D. S2CID 13871063. arXiv:physics/0611201 . doi:10.1016/j.cpc.2007.02.107.
Rastegari, Mohammad; Ordonez, Vicente; Redmon, Joseph; Farhadi, Ali. XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks. 2016. arXiv:1603.05279  [cs.CV].
Joshua V. Dillon; Ian Langmore; Dustin Tran; Eugene Brevdo; Srinivas Vasudevan; Dave Moore; Brian Patton; Alex Alemi; Matt Hoffman; Rif A. Saurous. TensorFlow Distributions (报告). 2017年11月28日. Bibcode:2017arXiv171110604D. arXiv:1711.10604 . Accessed May 23, 2018. All operations in TensorFlow Distributions are numerically stable across half, single, and double floating-point precisions (as TensorFlow dtypes: tf.bfloat16 (truncated floating point), tf.float16, tf.float32, tf.float64). Class constructors have a validate_args flag for numerical asserts
Abu Sebastian; Tomas Tuma; Nikolaos Papandreou; Manuel Le Gallo; Lukas Kull; Thomas Parnell; Evangelos Eleftheriou. Temporal correlation detection using computational phase-change memory. Nature Communications. 2017, 8 (1): 1115. Bibcode:2017NatCo...8.1115S. PMC 5653661 . PMID 29062022. arXiv:1706.00511 . doi:10.1038/s41467-017-01481-9.
Carlos Ríos; Nathan Youngblood; Zengguang Cheng; Manuel Le Gallo; Wolfram H.P. Pernice; C. David Wright; Abu Sebastian; Harish Bhaskaran. In-memory computing on a photonic platform. Science Advances. 2018, 5 (2): eaau5759. Bibcode:2019SciA....5.5759R. PMC 6377270 . PMID 30793028. S2CID 7637801. arXiv:1801.06228 . doi:10.1126/sciadv.aau5759.
Feldmann, J.; Youngblood, N.; Karpov, M.; et al. Parallel convolutional processing using an integrated photonic tensor. Nature. 2021, 589 (2): 52–58. PMID 33408373. S2CID 211010976. arXiv:2002.00281 . doi:10.1038/s41586-020-03070-1.
Joshi, Vinay; Le Gallo, Manuel; Haefeli, Simon; Boybat, Irem; Nandakumar, S. R.; Piveteau, Christophe; Dazzi, Martino; Rajendran, Bipin; Sebastian, Abu; Eleftheriou, Evangelos. Accurate deep neural network inference using computational phase-change memory. Nature Communications. 2020-05-18, 11 (1): 2473. Bibcode:2020NatCo..11.2473J. ISSN 2041-1723. PMC 7235046 . PMID 32424184. arXiv:1906.03138 . doi:10.1038/s41467-020-16108-9 .

cambricon.com

MLU 100 intelligence accelerator card. Cambricon. 2024 [2024年1月8日]. （原始内容存档于2021年11月10日）（Japanese）.

cnet.com

Rubin, Ben Fox. Qualcomm's Zeroth platform could make your smartphone much smarter. CNET. [2021年9月28日]. （原始内容存档于2024年10月10日）（英语）.

datanami.com

Woodie, Alex. Cerebras Hits the Accelerator for Deep Learning Workloads. Datanami. 2021-11-01 [2022-08-03].

doi.org

Jouppi, Norman P.; et al. In-Datacenter Performance Analysis of a Tensor Processing Unit. ACM SIGARCH Computer Architecture News. 2017-06-24, 45 (2): 1–12. arXiv:1704.04760 . doi:10.1145/3140659.3080246  （英语）.
Zhang, Wei. Parallel distributed processing model with local space-invariant interconnections and its optical architecture. Applied Optics. 1990, 29 (32): 4790–7. Bibcode:1990ApOpt..29.4790Z. PMID 20577468. doi:10.1364/AO.29.004790.
Asanović, K.; Beck, J.; Feldman, J.; Morgan, N.; Wawrzynek, J. Designing a connectionist network supercomputer. International Journal of Neural Systems (ResearchGate). 1994年1月, 4 (4): 317–26 [2023年12月26日]. PMID 8049794. doi:10.1142/S0129065793000250.
Gschwind, M.; Salapura, V.; Maischberger, O. A Generic Building Block for Hopfield Neural Networks with On-Chip Learning. 1996 IEEE International Symposium on Circuits and Systems. Circuits and Systems Connecting the World. ISCAS 96. 1996: 49–52. ISBN 0-7803-3073-0. S2CID 17630664. doi:10.1109/ISCAS.1996.598474.
Chen, Tianshi; Du, Zidong; Sun, Ninghui; Wang, Jia; Wu, Chengyong; Chen, Yunji; Temam, Olivier. DianNao. ACM SIGARCH Computer Architecture News. 2014-04-05, 42 (1): 269–284. ISSN 0163-5964. doi:10.1145/2654822.2541967 .
Chen, Yunji; Luo, Tao; Liu, Shaoli; Zhang, Shijin; He, Liqiang; Wang, Jia; Li, Ling; Chen, Tianshi; Xu, Zhiwei; Sun, Ninghui; Temam, Olivier. DaDianNao: A Machine-Learning Supercomputer. 2014 47th Annual IEEE/ACM International Symposium on Microarchitecture. IEEE. 2014年12月: 609–622. ISBN 978-1-4799-6998-2. S2CID 6838992. doi:10.1109/micro.2014.58.
Du, Zidong; Fasthuber, Robert; Chen, Tianshi; Ienne, Paolo; Li, Ling; Luo, Tao; Feng, Xiaobing; Chen, Yunji; Temam, Olivier. ShiDianNao. ACM SIGARCH Computer Architecture News. 2016-01-04, 43 (3S): 92–104. ISSN 0163-5964. doi:10.1145/2872887.2750389.
Liu, Daofu; Chen, Tianshi; Liu, Shaoli; Zhou, Jinhong; Zhou, Shengyuan; Teman, Olivier; Feng, Xiaobing; Zhou, Xuehai; Chen, Yunji. PuDianNao. ACM SIGARCH Computer Architecture News. 2015-05-29, 43 (1): 369–381. ISSN 0163-5964. doi:10.1145/2786763.2694358.
Chen, Yunji; Chen, Tianshi; Xu, Zhiwei; Sun, Ninghui; Temam, Olivier. DianNao family. Communications of the ACM. 2016-10-28, 59 (11): 105–112. ISSN 0001-0782. S2CID 207243998. doi:10.1145/2996864.
Gschwind, Michael; Hofstee, H. Peter; Flachs, Brian; Hopkins, Martin; Watanabe, Yukio; Yamazaki, Takeshi. Synergistic Processing in Cell's Multicore Architecture. IEEE Micro. 2006, 26 (2): 10–24. S2CID 17834015. doi:10.1109/MM.2006.41.
De Fabritiis, G. Performance of Cell processor for biomolecular simulations. Computer Physics Communications. 2007, 176 (11–12): 660–664. Bibcode:2007CoPhC.176..660D. S2CID 13871063. arXiv:physics/0611201 . doi:10.1016/j.cpc.2007.02.107.
Benthin, Carsten; Wald, Ingo; Scherbaum, Michael; Friedrich, Heiko. 2006 IEEE Symposium on Interactive Ray Tracing. 2006: 15–23. CiteSeerX 10.1.1.67.8982 . ISBN 978-1-4244-0693-7. S2CID 1198101. doi:10.1109/RT.2006.280210.
Kwon, Bomjun; Choi, Taiho; Chung, Heejin; Kim, Geonho. 2008 5th IEEE Consumer Communications and Networking Conference. 2008: 1030–1034. ISBN 978-1-4244-1457-4. S2CID 14429828. doi:10.1109/ccnc08.2007.235.
Duan, Rubing; Strey, Alfred. Euro-Par 2008 – Parallel Processing. Lecture Notes in Computer Science 5168. 2008: 665–675. ISBN 978-3-540-85450-0. doi:10.1007/978-3-540-85451-7_71.
Krizhevsky, A.; Sutskever, I.; Hinton, G.E. ImageNet Classification with Deep Convolutional Neural Networks. Communications of the ACM. 2017年5月24日, 60 (6): 84–90. doi:10.1145/3065386 .
Krizhevsky, Alex; Sutskever, Ilya; Hinton, Geoffrey E. ImageNet classification with deep convolutional neural networks. Communications of the ACM. 2017-05-24, 60 (6): 84–90. doi:10.1145/3065386  （英语）.
Sefat, Md Syadus; Aslan, Semih; Kellington, Jeffrey W; Qasem, Apan. Accelerating HotSpots in Deep Neural Networks on a CAPI-Based FPGA. 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). 2019年8月: 248–256. ISBN 978-1-7281-2058-4. S2CID 203656070. doi:10.1109/HPCC/SmartCity/DSS.2019.00048.
Abu Sebastian; Tomas Tuma; Nikolaos Papandreou; Manuel Le Gallo; Lukas Kull; Thomas Parnell; Evangelos Eleftheriou. Temporal correlation detection using computational phase-change memory. Nature Communications. 2017, 8 (1): 1115. Bibcode:2017NatCo...8.1115S. PMC 5653661 . PMID 29062022. arXiv:1706.00511 . doi:10.1038/s41467-017-01481-9.
Carlos Ríos; Nathan Youngblood; Zengguang Cheng; Manuel Le Gallo; Wolfram H.P. Pernice; C. David Wright; Abu Sebastian; Harish Bhaskaran. In-memory computing on a photonic platform. Science Advances. 2018, 5 (2): eaau5759. Bibcode:2019SciA....5.5759R. PMC 6377270 . PMID 30793028. S2CID 7637801. arXiv:1801.06228 . doi:10.1126/sciadv.aau5759.
Zhong Sun; Giacomo Pedretti; Elia Ambrosi; Alessandro Bricalli; Wei Wang; Daniele Ielmini. Solving matrix equations in one step with cross-point resistive arrays. Proceedings of the National Academy of Sciences. 2019, 116 (10): 4123–4128. Bibcode:2019PNAS..116.4123S. PMC 6410822 . PMID 30782810. doi:10.1073/pnas.1815682116 .
Marega, Guilherme Migliato; Zhao, Yanfei; Avsar, Ahmet; Wang, Zhenyu; Tripati, Mukesh; Radenovic, Aleksandra; Kis, Anras. Logic-in-memory based on an atomically thin semiconductor. Nature. 2020, 587 (2): 72–77. Bibcode:2020Natur.587...72M. PMC 7116757 . PMID 33149289. doi:10.1038/s41586-020-2861-0.
Feldmann, J.; Youngblood, N.; Karpov, M.; et al. Parallel convolutional processing using an integrated photonic tensor. Nature. 2021, 589 (2): 52–58. PMID 33408373. S2CID 211010976. arXiv:2002.00281 . doi:10.1038/s41586-020-03070-1.
Chen, Yu-Hsin; Emer, Joel; Sze, Vivienne. Eyeriss: A Spatial Architecture for Energy-Efficient Dataflow for Convolutional Neural Networks. IEEE Micro. 2017: 1. ISSN 0272-1732. doi:10.1109/mm.2017.265085944. hdl:1721.1/102369 .
Reagen, Brandon; Whatmough, Paul; Adolf, Robert; Rama, Saketh; Lee, Hyunkwang; Lee, Sae Kyu; Hernandez-Lobato, Jose Miguel; Wei, Gu-Yeon; Brooks, David. Minerva: Enabling Low-Power, Highly-Accurate Deep Neural Network Accelerators. 2016 ACM/IEEE 43rd Annual International Symposium on Computer Architecture (ISCA). 首尔: IEEE. 2016年6月: 267–278. ISBN 978-1-4673-8947-1. doi:10.1109/ISCA.2016.32.
Judd, Patrick; Albericio, Jorge; Moshovos, Andreas. Stripes: Bit-Serial Deep Neural Network Computing. IEEE Computer Architecture Letters. 2017-01-01, 16 (1): 80–83. ISSN 1556-6056. S2CID 3784424. doi:10.1109/lca.2016.2597140.
Jouppi, N.; Young, C.; Patil, N.; Patterson, D. In-Datacenter Performance Analysis of a Tensor Processing Unit. 计算机协会. 2017年6月24日: 1–12. ISBN 9781450348928. S2CID 4202768. doi:10.1145/3079856.3080246 .
Chi, Ping; Li, Shuangchen; Xu, Cong; Zhang, Tao; Zhao, Jishen; Liu, Yongpan; Wang, Yu; Xie, Yuan. PRIME: A Novel Processing-in-Memory Architecture for Neural Network Computation in ReRAM-Based Main Memory. 2016 ACM/IEEE 43rd Annual International Symposium on Computer Architecture (ISCA). IEEE. 2016年6月: 27–39. ISBN 978-1-4673-8947-1. doi:10.1109/isca.2016.13.
Song, Linghao; Qian, Xuehai; Li, Hai; Chen, Yiran. PipeLayer: A Pipelined ReRAM-Based Accelerator for Deep Learning. 2017 IEEE International Symposium on High Performance Computer Architecture (HPCA). IEEE. 2017年2月: 541–552. ISBN 978-1-5090-4985-1. S2CID 15281419. doi:10.1109/hpca.2017.55.
Shin, Dongjoo; Lee, Jinmook; Lee, Jinsu; Yoo, Hoi-Jun. 14.2 DNPU: An 8.1TOPS/W reconfigurable CNN-RNN processor for general-purpose deep neural networks. 2017 IEEE International Solid-State Circuits Conference (ISSCC). 2017: 240–241 [2023-08-24]. ISBN 978-1-5090-3758-2. S2CID 206998709. doi:10.1109/ISSCC.2017.7870350. （原始内容存档于2024-12-03）.
Lee, Jinmook; Kim, Changhyeon; Kang, Sanghoon; Shin, Dongjoo; Kim, Sangyeob; Yoo, Hoi-Jun. UNPU: A 50.6TOPS/W unified deep neural network accelerator with 1b-to-16b fully-variable weight bit-precision. 2018 IEEE International Solid - State Circuits Conference - (ISSCC). 2018: 218–220 [2023-11-30]. ISBN 978-1-5090-4940-0. S2CID 3861747. doi:10.1109/ISSCC.2018.8310262.
Liu, Shaoli; Du, Zidong; Tao, Jinhua; Han, Dong; Luo, Tao; Xie, Yuan; Chen, Yunji; Chen, Tianshi. Cambricon: An Instruction Set Architecture for Neural Networks. 2016 ACM/IEEE 43rd Annual International Symposium on Computer Architecture (ISCA). IEEE. 2016年6月: 393–405. ISBN 978-1-4673-8947-1. doi:10.1109/isca.2016.42.
Ambrogio, Stefano; Narayanan, Pritish; Tsai, Hsinyu; Shelby, Robert M.; Boybat, Irem; di Nolfo, Carmelo; Sidler, Severin; Giordano, Massimo; Bodini, Martina; Farinha, Nathan C. P.; Killeen, Benjamin. Equivalent-accuracy accelerated neural-network training using analogue memory. Nature. 2018年6月, 558 (7708): 60–67. Bibcode:2018Natur.558...60A. ISSN 0028-0836. PMID 29875487. S2CID 46956938. doi:10.1038/s41586-018-0180-5.
Chen, Wei-Hao; Lin, Wen-Jang; Lai, Li-Ya; Li, Shuangchen; Hsu, Chien-Hua; Lin, Huan-Ting; Lee, Heng-Yuan; Su, Jian-Wei; Xie, Yuan; Sheu, Shyh-Shyuan; Chang, Meng-Fan. A 16Mb dual-mode ReRAM macro with sub-14ns computing-in-memory and memory functions enabled by self-write termination scheme. 2017 IEEE International Electron Devices Meeting (IEDM). IEEE. 2017年12月: 28.2.1–28.2.4. ISBN 978-1-5386-3559-9. S2CID 19556846. doi:10.1109/iedm.2017.8268468.
Yang, J. Joshua; Strukov, Dmitri B.; Stewart, Duncan R. Memristive devices for computing. Nature Nanotechnology. 2013年1月, 8 (1): 13–24 [2025-02-28]. Bibcode:2013NatNa...8...13Y. ISSN 1748-3395. PMID 23269430. doi:10.1038/nnano.2012.240. （原始内容存档于2025-02-13）（英语）.
Shafiee, Ali; Nag, Anirban; Muralimanohar, Naveen; Balasubramonian, Rajeev; Strachan, John Paul; Hu, Miao; Williams, R. Stanley; Srikumar, Vivek. ISAAC. ACM SIGARCH Computer Architecture News. 2016-10-12, 44 (3): 14–26. ISSN 0163-5964. S2CID 6329628. doi:10.1145/3007787.3001139.
Nandakumar, S. R.; Boybat, Irem; Joshi, Vinay; Piveteau, Christophe; Le Gallo, Manuel; Rajendran, Bipin; Sebastian, Abu; Eleftheriou, Evangelos. Phase-Change Memory Models for Deep Learning Training and Inference. 2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS). IEEE. 2019年11月: 727–730. ISBN 978-1-7281-0996-1. S2CID 210930121. doi:10.1109/icecs46596.2019.8964852.
Joshi, Vinay; Le Gallo, Manuel; Haefeli, Simon; Boybat, Irem; Nandakumar, S. R.; Piveteau, Christophe; Dazzi, Martino; Rajendran, Bipin; Sebastian, Abu; Eleftheriou, Evangelos. Accurate deep neural network inference using computational phase-change memory. Nature Communications. 2020-05-18, 11 (1): 2473. Bibcode:2020NatCo..11.2473J. ISSN 2041-1723. PMC 7235046 . PMID 32424184. arXiv:1906.03138 . doi:10.1038/s41467-020-16108-9 .

eetimes.com

Google Developing AI Processors. （原始内容存档于2016-06-27）. Google using its own AI accelerators.

hal.science

inria.hal.science

Chellapilla, K.; Sidd Puri; Simard, P. High Performance Convolutional Neural Networks for Document Processing. 10th International Workshop on Frontiers in Handwriting Recognition. 2006年10月23日 [2023年12月23日].

handle.net

hdl.handle.net

Chen, Yu-Hsin; Emer, Joel; Sze, Vivienne. Eyeriss: A Spatial Architecture for Energy-Efficient Dataflow for Convolutional Neural Networks. IEEE Micro. 2017: 1. ISSN 0272-1732. doi:10.1109/mm.2017.265085944. hdl:1721.1/102369 .

harvard.edu

ui.adsabs.harvard.edu

Zhang, Wei. Parallel distributed processing model with local space-invariant interconnections and its optical architecture. Applied Optics. 1990, 29 (32): 4790–7. Bibcode:1990ApOpt..29.4790Z. PMID 20577468. doi:10.1364/AO.29.004790.
De Fabritiis, G. Performance of Cell processor for biomolecular simulations. Computer Physics Communications. 2007, 176 (11–12): 660–664. Bibcode:2007CoPhC.176..660D. S2CID 13871063. arXiv:physics/0611201 . doi:10.1016/j.cpc.2007.02.107.
Joshua V. Dillon; Ian Langmore; Dustin Tran; Eugene Brevdo; Srinivas Vasudevan; Dave Moore; Brian Patton; Alex Alemi; Matt Hoffman; Rif A. Saurous. TensorFlow Distributions (报告). 2017年11月28日. Bibcode:2017arXiv171110604D. arXiv:1711.10604 . Accessed May 23, 2018. All operations in TensorFlow Distributions are numerically stable across half, single, and double floating-point precisions (as TensorFlow dtypes: tf.bfloat16 (truncated floating point), tf.float16, tf.float32, tf.float64). Class constructors have a validate_args flag for numerical asserts
Abu Sebastian; Tomas Tuma; Nikolaos Papandreou; Manuel Le Gallo; Lukas Kull; Thomas Parnell; Evangelos Eleftheriou. Temporal correlation detection using computational phase-change memory. Nature Communications. 2017, 8 (1): 1115. Bibcode:2017NatCo...8.1115S. PMC 5653661 . PMID 29062022. arXiv:1706.00511 . doi:10.1038/s41467-017-01481-9.
Carlos Ríos; Nathan Youngblood; Zengguang Cheng; Manuel Le Gallo; Wolfram H.P. Pernice; C. David Wright; Abu Sebastian; Harish Bhaskaran. In-memory computing on a photonic platform. Science Advances. 2018, 5 (2): eaau5759. Bibcode:2019SciA....5.5759R. PMC 6377270 . PMID 30793028. S2CID 7637801. arXiv:1801.06228 . doi:10.1126/sciadv.aau5759.
Zhong Sun; Giacomo Pedretti; Elia Ambrosi; Alessandro Bricalli; Wei Wang; Daniele Ielmini. Solving matrix equations in one step with cross-point resistive arrays. Proceedings of the National Academy of Sciences. 2019, 116 (10): 4123–4128. Bibcode:2019PNAS..116.4123S. PMC 6410822 . PMID 30782810. doi:10.1073/pnas.1815682116 .
Marega, Guilherme Migliato; Zhao, Yanfei; Avsar, Ahmet; Wang, Zhenyu; Tripati, Mukesh; Radenovic, Aleksandra; Kis, Anras. Logic-in-memory based on an atomically thin semiconductor. Nature. 2020, 587 (2): 72–77. Bibcode:2020Natur.587...72M. PMC 7116757 . PMID 33149289. doi:10.1038/s41586-020-2861-0.
Ambrogio, Stefano; Narayanan, Pritish; Tsai, Hsinyu; Shelby, Robert M.; Boybat, Irem; di Nolfo, Carmelo; Sidler, Severin; Giordano, Massimo; Bodini, Martina; Farinha, Nathan C. P.; Killeen, Benjamin. Equivalent-accuracy accelerated neural-network training using analogue memory. Nature. 2018年6月, 558 (7708): 60–67. Bibcode:2018Natur.558...60A. ISSN 0028-0836. PMID 29875487. S2CID 46956938. doi:10.1038/s41586-018-0180-5.
Yang, J. Joshua; Strukov, Dmitri B.; Stewart, Duncan R. Memristive devices for computing. Nature Nanotechnology. 2013年1月, 8 (1): 13–24 [2025-02-28]. Bibcode:2013NatNa...8...13Y. ISSN 1748-3395. PMID 23269430. doi:10.1038/nnano.2012.240. （原始内容存档于2025-02-13）（英语）.
Joshi, Vinay; Le Gallo, Manuel; Haefeli, Simon; Boybat, Irem; Nandakumar, S. R.; Piveteau, Christophe; Dazzi, Martino; Rajendran, Bipin; Sebastian, Abu; Eleftheriou, Evangelos. Accurate deep neural network inference using computational phase-change memory. Nature Communications. 2020-05-18, 11 (1): 2473. Bibcode:2020NatCo..11.2473J. ISSN 2041-1723. PMC 7235046 . PMID 32424184. arXiv:1906.03138 . doi:10.1038/s41467-020-16108-9 .

huawei.com

consumer.huawei.com

HUAWEI Reveals the Future of Mobile AI at IFA. [2025-02-28]. （原始内容存档于2021-11-10）.

ieee.org

ieeexplore.ieee.org

Sefat, Md Syadus; Aslan, Semih; Kellington, Jeffrey W; Qasem, Apan. Accelerating HotSpots in Deep Neural Networks on a CAPI-Based FPGA. 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). 2019年8月: 248–256. ISBN 978-1-7281-2058-4. S2CID 203656070. doi:10.1109/HPCC/SmartCity/DSS.2019.00048.
Shin, Dongjoo; Lee, Jinmook; Lee, Jinsu; Yoo, Hoi-Jun. 14.2 DNPU: An 8.1TOPS/W reconfigurable CNN-RNN processor for general-purpose deep neural networks. 2017 IEEE International Solid-State Circuits Conference (ISSCC). 2017: 240–241 [2023-08-24]. ISBN 978-1-5090-3758-2. S2CID 206998709. doi:10.1109/ISSCC.2017.7870350. （原始内容存档于2024-12-03）.
Lee, Jinmook; Kim, Changhyeon; Kang, Sanghoon; Shin, Dongjoo; Kim, Sangyeob; Yoo, Hoi-Jun. UNPU: A 50.6TOPS/W unified deep neural network accelerator with 1b-to-16b fully-variable weight bit-precision. 2018 IEEE International Solid - State Circuits Conference - (ISSCC). 2018: 218–220 [2023-11-30]. ISBN 978-1-5090-4940-0. S2CID 3861747. doi:10.1109/ISSCC.2018.8310262.

spectrum.ieee.org

Photonic Chips Curb AI Training's Energy Appetite - IEEE Spectrum.

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convolutional neural network demo from 1993 featuring DSP32 accelerator. YouTube. 2014年6月2日 [2025年2月28日]. （原始内容存档于2016年5月8日）.
The end of general purpose computers (not). YouTube. 2015年4月17日 [2025年2月28日]. （原始内容存档于2018年1月10日）.