Minimizing Energy Under Performance Constraints on Embedded Platforms. - Connor Imes; Henry Hoffmann (EWiLi, 2014)

Minimizing energy under performance constraints on embedded platforms: resource allocation heuristics for homogeneous and single-ISA heterogeneous multi-cores. - Connor Imes; Henry Hoffmann (SIGBED Rev., 2014)

Racing and Pacing to Idle: Theoretical and Empirical Analysis of Energy Optimization Heuristics. - David H. K. Kim; Connor Imes; Henry Hoffmann (CPSNA, 2015)

POET: a portable approach to minimizing energy under soft real-time constraints. - Connor Imes; David H. K. Kim; Martina Maggio; Henry Hoffmann (RTAS, 2015)

Portable Multicore Resource Management for Applications with Performance Constraints. - Connor Imes; David H. K. Kim; Martina Maggio; Henry Hoffmann (MCSoC, 2016)

Bard: A unified framework for managing soft timing and power constraints. - Connor Imes; Henry Hoffmann (SAMOS, 2016)

A portable interface for runtime energy monitoring. - Connor Imes; Lars Bergstrom; Henry Hoffmann (SIGSOFT FSE, 2016)

CALOREE: Learning Control for Predictable Latency and Low Energy. - Nikita Mishra; Connor Imes; John D. Lafferty; Henry Hoffmann (ASPLOS, 2018)

Energy-efficient Application Resource Scheduling using Machine Learning Classifiers. - Connor Imes; Steven A. Hofmeyr; Henry Hoffmann (ICPP, 2018)

CoPPer: Soft Real-Time Application Performance Using Hardware Power Capping. - Connor Imes; Huazhe Zhang; Kevin Zhao; Henry Hoffmann (ICAC, 2019)

Proteus: Language and Runtime Support for Self-Adaptive Software Development. - Saeid Barati 001; Ferenc A. Bartha; Swarnendu Biswas; Robert Cartwright; Adam Duracz; Donald S. Fussell; Henry Hoffmann; Connor Imes; Jason E. Miller; Nikita Mishra; Arvind 001; Dung Nguyen; et al. (IEEE Softw., 2019)

Compiler Abstractions and Runtime for Extreme-scale SAR and CFD Workloads. - Connor Imes; Alexei Colin; Naifeng Zhang; Ajitesh Srivastava; Viktor K. Prasanna; John Paul Walters (ESPM2@SC, 2020)

Distributed and Heterogeneous SAR Backprojection with Halide. - Connor Imes; Tzu-Mao Li; Mark Glines; Rishi Khan; John Paul Walters (HPEC, 2021)

Pipeline Parallelism for Inference on Heterogeneous Edge Computing. - Yang Hu; Connor Imes; Xuanang Zhao; Souvik Kundu 002; Peter A. Beerel; Stephen P. Crago; John Paul Walters (CoRR, 2021)

PipeEdge: Pipeline Parallelism for Large-Scale Model Inference on Heterogeneous Edge Devices. - Yang Hu; Connor Imes; Xuanang Zhao; Souvik Kundu 002; Peter A. Beerel; Stephen P. Crago; John Paul Walters (DSD, 2022)

GOAL: Supporting General and Dynamic Adaptation in Computing Systems. - Ahsan Pervaiz; Yao-Hsiang Yang; Adam Duracz; Ferenc A. Bartha; Ryuichi Sai; Connor Imes; Robert Cartwright; Krishna V. Palem; Shan Lu 001; Henry Hoffmann (Onward!, 2022)

Distributed Edge Machine Learning Pipeline Scheduling with Reverse Auctions. - Connor Imes; David W. King; John Paul Walters (FMEC, 2023)

Quantpipe: Applying Adaptive Post-Training Quantization For Distributed Transformer Pipelines In Dynamic Edge Environments. - Haonan Wang; Connor Imes; Souvik Kundu 002; Peter A. Beerel; Stephen P. Crago; John Paul Walters (ICASSP, 2023)

Evaluating Deep Learning Recommendation Model Training Scalability with the Dynamic Opera Network. - Connor Imes; Andrew Rittenbach; Peng Xie; Dong-In Kang; John Paul Walters; Stephen P. Crago (EuroMLSys@EuroSys, 2024)