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Work item:
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L.IEDL
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Subject/title:
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Energy saving strategy for deep learning computing
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Status:
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Under study
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Approval process:
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AAP
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Type of work item:
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Recommendation
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Version:
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New
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Equivalent number:
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-
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Timing:
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2025 (Medium priority)
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Liaison:
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-
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Supporting members:
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China, China Unicom, China Telecom, Huazhong University of Science and Technology, Zhejiang Dahua Technology Ltd
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Summary:
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This recommendation identifies the energy saving strategy and technologies for deep learning AI computing procedure, and provides best practice recommendations when and how these technologies should be used in deep learning AI computing thereby reducing the AI computing center or AI computing platform system energy consumption.
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Comment:
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-
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Reference(s):
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Historic references:
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Contact(s):
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| ITU-T A.5 justification(s): |
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First registration in the WP:
2023-07-13 11:41:29
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Last update:
2024-07-04 15:27:37
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