Conference item
Evaluating and comparing the potentials in primary response for GPU and CPU data centers
- Abstract:
-
The rapid growth of Large Language Models (LLMs) and Artificial Intelligence (AI) has transformed traditional CPU-centric Data Centers (DaCe) into more powerdemanding GPU DaCes. Previous work has explored methods to reduce energy costs and carbon emissions in GPU DaCes. However, there remains a gap in understanding the potential of GPU DaCes for providing primary response, a crucial ancillary service for stabilizing the power system. Drawing on real-world job traces from a GPU-intensive DaCe operated by SenseTime and a CPU-intensive DaCe at Oak Ridge National Laboratory, we developed a mixed-integer linear programming model to assess the DaCe flexibility potentials considering individual jobs’ characteristics. We show that the GPU DaCe possesses a larger flexibility for delivering primary responses compared to the CPU DaCe. Furthermore, the GPU DaCe exhibits lower variability in flexibility across different times of the day and over a 7-month evaluation horizon, making them more dependable and stable sources for offering primary response.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 522.4KB, Terms of use)
-
- Publisher copy:
- 10.1109/pesgm51994.2024.10689061
Authors
- Funder identifier:
- https://ror.org/0439y7842
- Grant:
- EP/T028564/1
- Funder identifier:
- https://ror.org/019ya6433
- Grant:
- EP/S031901/1
- Publisher:
- IEEE
- Host title:
- 2024 IEEE Power & Energy Society General Meeting (PESGM)
- Journal:
- 2024 IEEE Power & Energy Society General Meeting (PESGM) More from this journal
- Publication date:
- 2024-10-04
- Acceptance date:
- 2024-07-21
- Event title:
- 2024 IEEE Power & Energy Society General Meeting (PESGM)
- Event location:
- Seattle
- Event website:
- https://pes-gm.org/seattle-2024/
- Event start date:
- 2024-07-21
- Event end date:
- 2024-07-25
- DOI:
- EISSN:
-
1944-9933
- ISSN:
-
1944-9925
- EISBN:
- 9798350381832
- ISBN:
- 9798350381849
- Language:
-
English
- Keywords:
- Pubs id:
-
2037626
- Local pid:
-
pubs:2037626
- Deposit date:
-
2024-10-10
Terms of use
- Copyright holder:
- IEEE
- Copyright date:
- 2024
- Rights statement:
- © 2024 IEEE.
- Notes:
- This is the accepted manuscript version of the article. The final version is available online from IEEE at https://dx.doi.org/10.1109/pesgm51994.2024.10689061| This is the accepted manuscript version of the article. The final version is available online from IEEE at https://doi.org/10.1109/pesgm51994.2024.10689061
If you are the owner of this record, you can report an update to it here: Report update to this record