张量处理单元 (Chinese Wikipedia)

Analysis of information sources in references of the Wikipedia article "张量处理单元" in Chinese language version.

refsWebsite

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24web.archive.org

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10cloud.google.com

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3doi.org

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2techradar.com

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2servethehome.com

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2arxiv.org

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2blog.google

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241.242

low place

2nih.gov

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2semanticscholar.org

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1googleblog.com

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1youtube.com

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1nytimes.com

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1pcworld.com

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1tomshardware.com

2,976^th place

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1computer.org

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1arstechnica.com

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1anandtech.com

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902^nd place

1top500.org

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1nextplatform.com

low place

41.242

176.9.41.242

Mirhoseini, Azalia; Goldie, Anna. A graph placement methodology for fast chip design (PDF). Nature. 2021-06-01, 594 (7962): 207–212 [2023-06-04]. PMID 35361999. S2CID 247855593. doi:10.1038/s41586-022-04657-6. （原始内容存档 (PDF)于2024-08-06）.
Mirhoseini, Azalia; Goldie, Anna. A graph placement methodology for fast chip design (PDF). Nature. 2021-06-01, 594 (7962): 207–212 [2023-06-04]. PMID 35361999. S2CID 247855593. doi:10.1038/s41586-022-04657-6. （原始内容存档 (PDF)于2024-08-06）.

anandtech.com

Frumusanu, Andre. Google I/O Opening Keynote Live-Blog. 8 May 2018 [9 May 2018]. （原始内容存档于2021-11-18）.

arstechnica.com

Bright, Peter. Google brings 45 teraflops tensor flow processors to its compute cloud. Ars Technica. 17 May 2017 [30 May 2017]. （原始内容存档于2022-03-06）.

arxiv.org

Jouppi, Norman P.; Kurian, George; Li, Sheng; Ma, Peter; Nagarajan, Rahul; Nai, Lifeng; Patil, Nishant; Subramanian, Suvinay; Swing, Andy; Towles, Brian; Young, Cliff; Zhou, Xiang; Zhou, Zongwei; Patterson, David. TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings. 2023. arXiv:2304.01433  [cs.AR].
Jouppi, Norman P.; Young, Cliff; Patil, Nishant; Patterson, David; Agrawal, Gaurav; Bajwa, Raminder; Bates, Sarah; Bhatia, Suresh; Boden, Nan; Borchers, Al; Boyle, Rick; Cantin, Pierre-luc; Chao, Clifford; Clark, Chris; Coriell, Jeremy; Daley, Mike; Dau, Matt; Dean, Jeffrey; Gelb, Ben; Ghaemmaghami, Tara Vazir; Gottipati, Rajendra; Gulland, William; Hagmann, Robert; Ho, C. Richard; Hogberg, Doug; Hu, John; Hundt, Robert; Hurt, Dan; Ibarz, Julian; Jaffey, Aaron; Jaworski, Alek; Kaplan, Alexander; Khaitan, Harshit; Koch, Andy; Kumar, Naveen; Lacy, Steve; Laudon, James; Law, James; Le, Diemthu; Leary, Chris; Liu, Zhuyuan; Lucke, Kyle; Lundin, Alan; MacKean, Gordon; Maggiore, Adriana; Mahony, Maire; Miller, Kieran; Nagarajan, Rahul; Narayanaswami, Ravi; Ni, Ray; Nix, Kathy; Norrie, Thomas; Omernick, Mark; Penukonda, Narayana; Phelps, Andy; Ross, Jonathan; Ross, Matt; Salek, Amir; Samadiani, Emad; Severn, Chris; Sizikov, Gregory; Snelham, Matthew; Souter, Jed; Steinberg, Dan; Swing, Andy; Tan, Mercedes; Thorson, Gregory; Tian, Bo; Toma, Horia; Tuttle, Erick; Vasudevan, Vijay; Walter, Richard; Wang, Walter; Wilcox, Eric; Yoon, Doe Hyun. In-Datacenter Performance Analysis of a Tensor Processing Unit™. Toronto, Canada. June 26, 2017. arXiv:1704.04760 .

blog.google

Ironwood: The first Google TPU for the age of inference. Google Blog. 9 April 2025 [2025-04-09]. （原始内容存档于2025-05-03）（英语）.
Ironwood: The first Google TPU for the age of inference. Google Cloud Blog. [2025-04-09] （美国英语）.

cloud.google.com

云张量处理单元 (TPU) | Cloud TPU. Google Cloud. [2020-07-20]. （原始内容存档于2021-06-13）（中文（中国大陆））.
System Architecture | Cloud TPU. Google Cloud. [2022-12-11]. （原始内容存档于2022-12-11）（英语）.
Stay tuned, more information on TPU v4 is coming soon （页面存档备份，存于互联网档案馆）, retrieved 2020-08-06.
Cloud TPU v5e Inference Public Preview, retrieved 2023-11-06.
Cloud TPU v5p （页面存档备份，存于互联网档案馆） Google Cloud. retrieved 2024-04-09
Cloud TPU v5p Training （页面存档备份，存于互联网档案馆）, retrieved 2024-04-09.
Introducing Trillium, sixth-generation TPUs. Google Cloud Blog. [2024-05-29] （美国英语）.
TPU v6e. Google Cloud. [2024-11-10]. （原始内容存档于2025-05-10）（英语）.
Introducing Trillium, sixth-generation TPUs. Google Cloud Blog. [2024-05-17]. （原始内容存档于2025-05-07）（美国英语）.
Cloud TPU. Google Cloud. [2021-05-21]. （原始内容存档于2025-05-06）（英语）.

computer.org

conferences.computer.org

Jouppi, Norman P.; Yoon, Doe Hyun; Ashcraft, Matthew; Gottscho, Mark. Ten lessons from three generations that shaped Google's TPUv4i (PDF). International Symposium on Computer Architecture. Valencia, Spain. June 14, 2021 [2025-05-04]. ISBN 978-1-4503-9086-6. doi:10.1109/ISCA52012.2021.00010. （原始内容 (PDF)存档于2021-06-09）.

doi.org

Jouppi, Norman P.; Yoon, Doe Hyun; Ashcraft, Matthew; Gottscho, Mark. Ten lessons from three generations that shaped Google's TPUv4i (PDF). International Symposium on Computer Architecture. Valencia, Spain. June 14, 2021 [2025-05-04]. ISBN 978-1-4503-9086-6. doi:10.1109/ISCA52012.2021.00010. （原始内容 (PDF)存档于2021-06-09）.
Mirhoseini, Azalia; Goldie, Anna. A graph placement methodology for fast chip design (PDF). Nature. 2021-06-01, 594 (7962): 207–212 [2023-06-04]. PMID 35361999. S2CID 247855593. doi:10.1038/s41586-022-04657-6. （原始内容存档 (PDF)于2024-08-06）.
Mirhoseini, Azalia; Goldie, Anna. A graph placement methodology for fast chip design (PDF). Nature. 2021-06-01, 594 (7962): 207–212 [2023-06-04]. PMID 35361999. S2CID 247855593. doi:10.1038/s41586-022-04657-6. （原始内容存档 (PDF)于2024-08-06）.

googleblog.com

cloudplatform.googleblog.com

Jouppi, Norm. Google supercharges machine learning tasks with TPU custom chip. Google Cloud Platform Blog. May 18, 2016 [2017-01-22]. （原始内容存档于2016-05-18）（美国英语）.

nextplatform.com

Teich, Paul. Tearing Apart Google's TPU 3.0 AI Coprocessor. The Next Platform. 10 May 2018 [14 May 2018]. （原始内容存档于2022-05-15）.

nih.gov

ncbi.nlm.nih.gov

Mirhoseini, Azalia; Goldie, Anna. A graph placement methodology for fast chip design (PDF). Nature. 2021-06-01, 594 (7962): 207–212 [2023-06-04]. PMID 35361999. S2CID 247855593. doi:10.1038/s41586-022-04657-6. （原始内容存档 (PDF)于2024-08-06）.
Mirhoseini, Azalia; Goldie, Anna. A graph placement methodology for fast chip design (PDF). Nature. 2021-06-01, 594 (7962): 207–212 [2023-06-04]. PMID 35361999. S2CID 247855593. doi:10.1038/s41586-022-04657-6. （原始内容存档 (PDF)于2024-08-06）.

nytimes.com

Google Makes Its Special A.I. Chips Available to Others. The New York Times. [2018-02-12]. （原始内容存档于2022-04-08）（英语）.

pcworld.com

Google's Tensor Processing Unit could advance Moore's Law 7 years into the future. PCWorld. [2017-01-19]. （原始内容存档于2019-02-18）（英语）.

semanticscholar.org

api.semanticscholar.org

Mirhoseini, Azalia; Goldie, Anna. A graph placement methodology for fast chip design (PDF). Nature. 2021-06-01, 594 (7962): 207–212 [2023-06-04]. PMID 35361999. S2CID 247855593. doi:10.1038/s41586-022-04657-6. （原始内容存档 (PDF)于2024-08-06）.
Mirhoseini, Azalia; Goldie, Anna. A graph placement methodology for fast chip design (PDF). Nature. 2021-06-01, 594 (7962): 207–212 [2023-06-04]. PMID 35361999. S2CID 247855593. doi:10.1038/s41586-022-04657-6. （原始内容存档 (PDF)于2024-08-06）.

servethehome.com

Kennedy, Patrick. Case Study on the Google TPU and GDDR5 from Hot Chips 29. Serve The Home. 22 August 2017 [23 August 2017]. （原始内容存档于2021-11-23）.
Kennedy, Patrick. Google Cloud TPU Details Revealed. Serve The Home. 17 May 2017 [30 May 2017]. （原始内容存档于2022-06-12）.

techradar.com

Google's Tensor Processing Unit explained: this is what the future of computing looks like. TechRadar. [2017-01-19]. （原始内容存档于2022-02-26）（英语）.
Afifi-Sabet, Keumars. Google is rapidly turning into a formidable opponent to BFF Nvidia — the TPU v5p AI chip powering its hypercomputer is faster and has more memory and bandwidth than ever before, beating even the mighty H100. TechRadar. 2023-12-23 [2024-04-08]. （原始内容存档于2025-02-11）.

tomshardware.com

Armasu, Lucian. Google's Big Chip Unveil For Machine Learning: Tensor Processing Unit With 10x Better Efficiency (Updated). Tom's Hardware. 2016-05-19 [2016-06-26].

top500.org

Feldman, Michael. Google Offers Glimpse of Third-Generation TPU Processor. Top 500. 11 May 2018 [14 May 2018]. （原始内容存档于2021-11-18）.

web.archive.org

云张量处理单元 (TPU) | Cloud TPU. Google Cloud. [2020-07-20]. （原始内容存档于2021-06-13）（中文（中国大陆））.
Google's Tensor Processing Unit explained: this is what the future of computing looks like. TechRadar. [2017-01-19]. （原始内容存档于2022-02-26）（英语）.
Jouppi, Norm. Google supercharges machine learning tasks with TPU custom chip. Google Cloud Platform Blog. May 18, 2016 [2017-01-22]. （原始内容存档于2016-05-18）（美国英语）.
"TensorFlow: Open source machine learning" （页面存档备份，存于互联网档案馆） "It is machine learning software being used for various kinds of perceptual and language understanding tasks" — Jeffrey Dean, minute 0:47 / 2:17 from Youtube clip
Google Makes Its Special A.I. Chips Available to Others. The New York Times. [2018-02-12]. （原始内容存档于2022-04-08）（英语）.
Google's Tensor Processing Unit could advance Moore's Law 7 years into the future. PCWorld. [2017-01-19]. （原始内容存档于2019-02-18）（英语）.
Jouppi, Norman P.; Yoon, Doe Hyun; Ashcraft, Matthew; Gottscho, Mark. Ten lessons from three generations that shaped Google's TPUv4i (PDF). International Symposium on Computer Architecture. Valencia, Spain. June 14, 2021 [2025-05-04]. ISBN 978-1-4503-9086-6. doi:10.1109/ISCA52012.2021.00010. （原始内容 (PDF)存档于2021-06-09）.
System Architecture | Cloud TPU. Google Cloud. [2022-12-11]. （原始内容存档于2022-12-11）（英语）.
Kennedy, Patrick. Case Study on the Google TPU and GDDR5 from Hot Chips 29. Serve The Home. 22 August 2017 [23 August 2017]. （原始内容存档于2021-11-23）.
Stay tuned, more information on TPU v4 is coming soon （页面存档备份，存于互联网档案馆）, retrieved 2020-08-06.
Cloud TPU v5p （页面存档备份，存于互联网档案馆） Google Cloud. retrieved 2024-04-09
Cloud TPU v5p Training （页面存档备份，存于互联网档案馆）, retrieved 2024-04-09.
TPU v6e. Google Cloud. [2024-11-10]. （原始内容存档于2025-05-10）（英语）.
Ironwood: The first Google TPU for the age of inference. Google Blog. 9 April 2025 [2025-04-09]. （原始内容存档于2025-05-03）（英语）.
Bright, Peter. Google brings 45 teraflops tensor flow processors to its compute cloud. Ars Technica. 17 May 2017 [30 May 2017]. （原始内容存档于2022-03-06）.
Kennedy, Patrick. Google Cloud TPU Details Revealed. Serve The Home. 17 May 2017 [30 May 2017]. （原始内容存档于2022-06-12）.
Frumusanu, Andre. Google I/O Opening Keynote Live-Blog. 8 May 2018 [9 May 2018]. （原始内容存档于2021-11-18）.
Feldman, Michael. Google Offers Glimpse of Third-Generation TPU Processor. Top 500. 11 May 2018 [14 May 2018]. （原始内容存档于2021-11-18）.
Teich, Paul. Tearing Apart Google's TPU 3.0 AI Coprocessor. The Next Platform. 10 May 2018 [14 May 2018]. （原始内容存档于2022-05-15）.
Mirhoseini, Azalia; Goldie, Anna. A graph placement methodology for fast chip design (PDF). Nature. 2021-06-01, 594 (7962): 207–212 [2023-06-04]. PMID 35361999. S2CID 247855593. doi:10.1038/s41586-022-04657-6. （原始内容存档 (PDF)于2024-08-06）.
Afifi-Sabet, Keumars. Google is rapidly turning into a formidable opponent to BFF Nvidia — the TPU v5p AI chip powering its hypercomputer is faster and has more memory and bandwidth than ever before, beating even the mighty H100. TechRadar. 2023-12-23 [2024-04-08]. （原始内容存档于2025-02-11）.
Mirhoseini, Azalia; Goldie, Anna. A graph placement methodology for fast chip design (PDF). Nature. 2021-06-01, 594 (7962): 207–212 [2023-06-04]. PMID 35361999. S2CID 247855593. doi:10.1038/s41586-022-04657-6. （原始内容存档 (PDF)于2024-08-06）.
Introducing Trillium, sixth-generation TPUs. Google Cloud Blog. [2024-05-17]. （原始内容存档于2025-05-07）（美国英语）.
Cloud TPU. Google Cloud. [2021-05-21]. （原始内容存档于2025-05-06）（英语）.

youtube.com

"TensorFlow: Open source machine learning" （页面存档备份，存于互联网档案馆） "It is machine learning software being used for various kinds of perceptual and language understanding tasks" — Jeffrey Dean, minute 0:47 / 2:17 from Youtube clip