| Optimizing grouped convolutions on edge devices P Gibson, J Cano, J Turner, EJ Crowley, M O’Boyle, A Storkey 2020 IEEE 31st International Conference on Application-specific Systems …, 2020 | 26 | 2020 |
| Secda: Efficient hardware/software co-design of fpga-based dnn accelerators for edge inference J Haris, P Gibson, J Cano, NB Agostini, D Kaeli 2021 IEEE 33rd International Symposium on Computer Architecture and High …, 2021 | 15 | 2021 |
| Transfer-tuning: Reusing auto-schedules for efficient tensor program code generation P Gibson, J Cano Proceedings of the International Conference on Parallel Architectures and …, 2022 | 12 | 2022 |
| Assessing robustness of image recognition models to changes in the computational environment N Louloudakis, P Gibson, J Cano, A Rajan NeurIPS ML Safety Workshop, 2022 | 7 | 2022 |
| Bifrost: End-to-End Evaluation and Optimization of Reconfigurable DNN Accelerators A Stjerngren, P Gibson, J Cano 2022 IEEE International Symposium on Performance Analysis of Systems and …, 2022 | 5 | 2022 |
| SECDA-TFLite: A toolkit for efficient development of FPGA-based DNN accelerators for edge inference J Haris, P Gibson, J Cano, NB Agostini, D Kaeli Journal of Parallel and Distributed Computing 173, 140-151, 2023 | 4 | 2023 |
| Fault Localization for Buggy Deep Learning Framework Conversions in Image Recognition N Louloudakis, P Gibson, J Cano, A Rajan 2023 38th IEEE/ACM International Conference on Automated Software …, 2023 | 3 | 2023 |
| Exploring effects of computational parameter changes to image recognition systems N Louloudakis, P Gibson, J Cano, A Rajan arXiv preprint arXiv:2211.00471, 2022 | 3 | 2022 |
| ICE-Pick: Iterative Cost-Efficient Pruning for DNNs W Hu, P Gibson, J Cano ICML 2023 Workshop Neural Compression: From Information Theory to Applications, 2023 | 2 | 2023 |
| Productive Reproducible Workflows for DNNs: A Case Study for Industrial Defect Detection P Gibson, J Cano arXiv preprint arXiv:2206.09359, 2022 | 2 | 2022 |
| Orpheus: A New Deep Learning Framework for Easy Deployment and Evaluation of Edge Inference P Gibson, J Cano 2020 IEEE International Symposium on Performance Analysis of Systems and …, 2020 | 2 | 2020 |
| Deep learning on a low power gpu P Gibson University of Edinburgh, Project Archive, 2019 | 2 | 2019 |
| AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators NB Agostini, J Haris, P Gibson, M Jayaweera, N Rubin, A Tumeo, ... 2024 IEEE/ACM International Symposium on Code Generation and Optimization …, 2024 | 1 | 2024 |
| DLAS: An Exploration and Assessment of the Deep Learning Acceleration Stack P Gibson, J Cano, EJ Crowley, A Storkey, M O'Boyle arXiv preprint arXiv:2311.08909, 2023 | 1 | 2023 |
| DeltaNN: Assessing the impact of computational environment parameters on the performance of image recognition models N Louloudakis, P Gibson, J Cano, A Rajan 2023 IEEE International Conference on Software Maintenance and Evolution …, 2023 | 1 | 2023 |
| Fix-Con: Automatic Fault Localization and Repair of Deep Learning Model Conversions N Louloudakis, P Gibson, J Cano, A Rajan arXiv preprint arXiv:2312.15101, 2023 | | 2023 |
| AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators N Bohm Agostini, J Haris, P Gibson, M Jayaweera, N Rubin, A Tumeo, ... arXiv e-prints, arXiv: 2312.14821, 2023 | | 2023 |
| Fault Localization for Framework Conversions of Image Recognition Models N Louloudakis, P Gibson, J Cano, A Rajan arXiv preprint arXiv:2306.06157, 2023 | | 2023 |
| A Differential Testing Framework to Evaluate Image Recognition Model Robustness N Louloudakis, P Gibson, J Cano, A Rajan arXiv preprint arXiv:2306.06208, 2023 | | 2023 |
| MutateNN: Mutation Testing of Image Recognition Models Deployed on Hardware Accelerators N Louloudakis, P Gibson, J Cano, A Rajan arXiv preprint arXiv:2306.01697, 2023 | | 2023 |
Jude HarisUniversity of GlasgowVerified email at research.gla.ac.uk
