[IISWC-2022] Understanding the Power of Evolutionary Computation for GPU Code Optimization

• Jhe-Yu Liou, Muaaz Awan, Steven Hofmeyr, Stephanie Forrest, Carole-Jean Wu. In Proceedings of the IEEE International Symposium on Workload Characterization (IISWC), 2022.

[GECCO 2020] GEVO-ML: A Proposal for Optimizing ML Code with Evolutionary Computation

• Jhe-Yu Liou, Xiaodong Wang, Stephanie Forrest, and Carole-Jean Wu. In Proceedings of the Genetic and Evolutionary Computation Conference Neuroevolution at Work (GECCO-NEvo@Work) , 2020.

[TACO 2020] GEVO: GPU Code Optimization Using Evolutionary Computation

• Jhe-Yu Liou, Xiaodong Wang, Stephanie Forrest, and Carole-Jean Wu. In Proceedings of the ACM Transactions on Architecture and Code Optimization (TACO), 2020.

[ASPLOS WACI 2019] Uncovering Performance Opportunities by Relaxing Program Semantics of GPGPU Kernels

• Jhe-Yu Liou, Stephanie Forrest, and Carole-Jean Wu. In the 24th ACM International Conference on Architectural Support for Programming Languages and Operating Systems Wild And Crazy Ideas Track (ASPLOS WACI), 2019.

[ICSE GI 2019] Genetic Improvement of GPU Code

• Jhe-Yu Liou, Stephanie Forrest, and Carole-Jean Wu. In Proceedings of the Annual Workshop on Genetic Improvement (GI) in conjunction with ICSE, 2019.

Received the 2019 ICSE Genetic Improvement on Software Best Paper Award

[HPCA 2019] Understanding the Future of Energy Efficiency in Multi-Module GPUs

• Akhil Arunkumar, Evgeny Bolotin, David Nellans, and Carole-Jean Wu. In Proceedings of the 25th IEEE International Symposium on High Performance Computer Architecture, 2019.

[HPCA 2018] LATTE-CC: Latency Tolerance Aware Adaptive Cache Compression Management for Energy Efficient GPUs

• Akhil Arunkumar, Shin-Ying Lee, Vignesh Soundararajan, and Carole-Jean Wu. In Proceedings of the 24th IEEE International Symposium on High Performance Computer Architecture, 2018.

[IISWC 2017] Performance Characterization, Prediction, and Optimization for Heterogeneous Systems with Multi-Level Memory Interference

• Shin-Ying Lee, and Carole-Jean Wu. In Proceedings of the IEEE International Symposium on Workload Characterization, 2017.

[ISCA 2017] MCM-GPU: Multi-Chip-Module GPUs for Continued Performance Scalability

• Akhil Arunkumar, Evgeny Bolotin, Benjamin Cho, Ugljesa Milic, Eiman Ebrahimi, Oreste Villa, Aamer Jaleel, Carole-Jean Wu, and David Nellans. In Proceedings of the 44th International Symposium on Computer Architecture, 2017.

[ICCD 2016] Ctrl-C: Instruction-Aware Control Loop Based Adaptive Cache Bypassing for GPUs

• Shin-Ying Lee and Carole-Jean Wu. In Proceedings of the IEEE International Conference on Computer Design, 2016.

[IISWC 2016] ID-Cache: Instruction and Memory Divergence Based Cache Management for GPUs

• Akhil Arunkumar, Shin-Ying Lee, and Carole-Jean Wu. In Proceedings of the IEEE International Symposium on Workload Characterization, 2016.

[ISCA 2015] CAWA: Coordinated Warp Scheduling and Cache Prioritization for Critical Warp Acceleration of GPGPU Workloads

• Shin-Ying Lee, Akhil Arunkumar, and Carole-Jean Wu. In Proceedings of the 42nd International Symposium on Computer Architecture, 2015.

[PACT 2014] CAWS: Criticality-Aware Warp Scheduling for GPGPU Workloads

• Shin-Ying Lee and Carole-Jean Wu. In Proceedings of the 23rd International Conference on Parallel Architectures and Compilation Techniques, 2014.

[ISPASS 2014] Characterizing the Latency Hiding Ability of GPUs

• Shin-Ying Lee and Carole-Jean Wu. In Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software as a poster abstract, 2014.