Connor Imes
Connor Imes
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Cited by
Cited by
POET: a portable approach to minimizing energy under soft real-time constraints
C Imes, DHK Kim, M Maggio, H Hoffmann
21st IEEE Real-Time and Embedded Technology and Applications Symposium, 75-86, 2015
CALOREE: Learning control for predictable latency and low energy
N Mishra, C Imes, JD Lafferty, H Hoffmann
ACM SIGPLAN Notices 53 (2), 184-198, 2018
Racing and pacing to idle: Theoretical and empirical analysis of energy optimization heuristics
DHK Kim, C Imes, H Hoffmann
2015 IEEE 3rd international conference on cyber-physical systems, networks …, 2015
Energy-efficient application resource scheduling using machine learning classifiers
C Imes, S Hofmeyr, H Hoffmann
Proceedings of the 47th International Conference on Parallel Processing, 1-11, 2018
Minimizing energy under performance constraints on embedded platforms: resource allocation heuristics for homogeneous and single-ISA heterogeneous multi-cores
C Imes, H Hoffmann
ACM SIGBED Review 11 (4), 49-54, 2015
Copper: Soft real-time application performance using hardware power capping
C Imes, H Zhang, K Zhao, H Hoffmann
2019 IEEE International Conference on Autonomic Computing (ICAC), 31-41, 2019
Bard: A unified framework for managing soft timing and power constraints
C Imes, H Hoffmann
2016 International Conference on Embedded Computer Systems: Architectures …, 2016
Proteus: Language and runtime support for self-adaptive software development
S Barati, FA Bartha, S Biswas, R Cartwright, A Duracz, D Fussell, ...
IEEE Software 36 (2), 73-82, 2019
A portable interface for runtime energy monitoring
C Imes, L Bergstrom, H Hoffmann
Proceedings of the 2016 24th ACM SIGSOFT International Symposium on …, 2016
Portable multicore resource management for applications with performance constraints
C Imes, DHK Kim, M Maggio, H Hoffmann
2016 IEEE 10th International Symposium on Embedded Multicore/Many-core …, 2016
Handing dvfs to hardware: Using power capping to control software performance
C Imes, H Zhang, K Zhao, H Hoffmann
Technical Report, 2018
Pipeline Parallelism for Inference on Heterogeneous Edge Computing
Y Hu, C Imes, X Zhao, S Kundu, PA Beerel, SP Crago, JPN Walters
arXiv preprint arXiv:2110.14895, 2021
PipeEdge: Pipeline Parallelism for Large-Scale Model Inference on Heterogeneous Edge Devices
Y Hu, C Imes, X Zhao, S Kundu, PA Beerel, SP Crago, JP Walters
2022 25th Euromicro Conference on Digital System Design (DSD), 298-307, 2022
A Case Study and Characterization of a Many-socket, Multi-tier NUMA HPC Platform
C Imes, S Hofmeyr, DID Kang, JP Walters
2020 IEEE/ACM 6th Workshop on the LLVM Compiler Infrastructure in HPC (LLVM …, 2020
Compiler abstractions and runtime for extreme-scale sar and cfd workloads
C Imes, A Colin, N Zhang, A Srivastava, V Prasanna, JP Walters
2020 IEEE/ACM Fifth International Workshop on Extreme Scale Programming …, 2020
A Portable Interface for Runtime Energy Monitoring: Extended Analysis
C Imes, L Bergstrom, H Hoffmann
Tech. rep. TR-2016-08. University of Chicago, Department of Computer Science, 2016
Minimizing Energy Under Performance Constraints on Embedded Platforms.
C Imes, H Hoffmann
EWiLi, 2014
Quantpipe: Applying Adaptive Post-Training Quantization For Distributed Transformer Pipelines In Dynamic Edge Environments
H Wang, C Imes, S Kundu, PA Beerel, SP Crago, JP Walters
ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023
Balancing performance and energy in computing systems
CK Imes
The University of Chicago, 2018
Energy Efficiency in HPC with Machine Learning and Control Theory
C Imes, S Hofmeyr, H Hofmann
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