Connor Imes

2024

Andrew Rittenbach, Connor Imes, and John Paul Walters. Timely Wildfire Perimeter Mapping for Unmanned Aerial Platforms. In: Optica Imaging Congress 2024 (3D, AOMS, COSI, ISA, pcAOP). 2024.

Connor Imes, Andrew Rittenbach, Peng Xie, Dong In D. Kang, John Paul Walters, Stephen P. Crago. Evaluating Deep Learning Recommendation Model Training Scalability with the Dynamic Opera Network. In: EuroMLSys. 2024.

2023

Connor Imes, David W. King, John Paul Walters. Distributed Edge Machine Learning Pipeline Scheduling with Reverse Auctions. In: FMEC. 2023. [Best Paper Award]

Haonan Wang, Connor Imes, Souvik Kundu, Peter A. Beerel, Stephen P. Crago, John Paul Walters. QuantPipe: Applying Adaptive Post-Training Quantization for Distributed Transformer Pipelines in Dynamic Edge Environments. In: ICASSP. 2023.

2022

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

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

2021

Connor Imes, Tzu-Mao Li, Mark Glines, Rishi Khan, John Paul Walters. Distributed and Heterogeneous SAR Backprojection with Halide. In: HPEC. 2021. [Outstanding Paper Award]

2020

Connor Imes, Alexei Colin, Naifeng Zhang, Ajitesh Srivastava, Viktor Prasanna, John Paul Walters. Compiler Abstractions and Runtime for Extreme-scale SAR and CFD Workloads. In: ESPM2. 2020.

Connor Imes, Steven Hofmeyr, Dong In D. Kang, John Paul Walters. A Case Study and Characterization of a Many-socket, Multi-tier NUMA HPC Platform. In: HiPar. 2020.

2019

Connor Imes, Huazhe Zhang, Kevin Zhao, and Henry Hoffmann. CoPPer: Soft Real-time Application Performance Using Hardware Power Capping. In: ICAC. 2019. [Best Paper Award]

Saeid Barati, Ferenc A. Bartha, Swarnendu Biswas, Robert Cartwright, Adam Duracz, Donald Fussell, Henry Hoffmann, Connor Imes, Jason Miller, Nikita Mishra, Arvind, Dung Nguyen, Krishna V. Palem, Yan Pei, Keshav Pingali, Ryuichi Sai, Andrew Wright, Yao-Hsiang Yang, Sizhuo Zhang. Proteus: Language and Runtime Support for Self-Adaptive Software Development. In: IEEE Software, vol. 36, no. 2, pp. 73-82. March-April 2019.

2018

Connor Imes, Steven Hofmeyr, and Henry Hoffmann. Energy-efficient Application Resource Scheduling using Machine Learning Classifiers. In: ICPP. 2018.

Nikita Mishra, Connor Imes, John Lafferty, and Henry Hoffmann. Controlling AI Engines in Dynamic Environments. In: SysML Conference. 2018.

Nikita Mishra, Connor Imes, John Lafferty, and Henry Hoffmann. CALOREE: Learning Control for Predictable Latency and Low Energy. In: ASPLOS. 2018. [2019 IEEE Micro Top Pick Honorable Mention]

2016

Connor Imes, Lars Bergstrom, and Henry Hoffmann. A Portable Interface for Runtime Energy Monitoring. In: FSE. 2016.

Connor Imes, David H. K. Kim, Martina Maggio, and Henry Hoffmann. Portable Multicore Resource Management for Applications with Performance Constraints. In: MCSoC. 2016.

Connor Imes and Henry Hoffmann. Bard: A Unified Framework for Managing Soft Timing and Power Constraints. In: SAMOS. 2016.

2015

David H. K. Kim, Connor Imes, and Henry Hoffmann. Racing and Pacing to Idle: Multicore Energy Optimization Under Performance Constraints. In: CPSNA. 2015.

Connor Imes, David H. K. Kim, Martina Maggio, and Henry Hoffmann. POET: A Portable Approach to Minimizing Energy Under Soft Real-time Constraints. In: RTAS. 2015.

2014

Connor Imes and Henry Hoffmann. Minimizing Energy Under Performance Constraints on Embedded Platforms: Resource Allocation Heuristics for Homogeneous and Single-ISA Heterogeneous Multi-Cores. In: SIGBED Review. 2014. [Best Paper Award]