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Comparing Power Signatures of HPC Workloads: Machine Learni..:

, In: Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis,

Govind, Anish ; Bhalachandra, Sridutt ; Zhao, Zhengji... - p. 1890-1893 , 2023

Link: https://dl.acm.org/doi/10.1145/3624062.3624274

RT 
T1 <cTitle>Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis</cTitle>: T1 <Title>Comparing Power Signatures of HPC Workloads: Machine Learning vs Simulation</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3624274&Exemplar=1&LAN=DE
				
A1 Govind, Anish
A1 Bhalachandra, Sridutt
A1 Zhao, Zhengji
A1 Rrapaj, Ermal
A1 Austin, Brian
A1 Nam, Hai Ah
PB ACM
YR 2023
K1 automatic demand response
K1 exascale systems
K1 machine learning workloads
K1 modeling workloads
K1 power analysis
K1 power signature
K1 simulation workloads
K1 super computing
K1 sustainable supercomputing
K1 General and reference
K1 Networks
K1 Computing methodologies
K1 Computer systems organization
K1 Software and its engineering
K1 Cross-computing tools and techniques
K1 Modeling and simulation
K1 Architectures
K1 Performance
K1 Parallel architectures
K1 Multicore architectures
SP 1890
OP 1893
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3624062.3624274
DO https://dl.acm.org/doi/10.1145/3624062.3624274
SF ELIB - SuUB Bremen

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