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Perry Gibson
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2020 – today
- 2025
- [c10]Aidan Ferguson, Perry Gibson, Lara D'Agata, Parker McLeod, Ferhat Yaman, Amitabh Das, Ian Colbert, José Cano:
Exploiting Unstructured Sparsity in Fully Homomorphic Encrypted DNNs. EuroMLSys 2025: 31-38 - [c9]Nikolaos Louloudakis, Perry Gibson, José Cano, Ajitha Rajan:
Exploring Robustness of Image Recognition Models on Hardware Accelerators. ICSTW 2025: 368-374 - [i14]Aidan Ferguson, Perry Gibson, Lara D'Agata, Parker McLeod, Ferhat Yaman, Amitabh Das, Ian Colbert, José Cano:
Exploiting Unstructured Sparsity in Fully Homomorphic Encrypted DNNs. CoRR abs/2503.09184 (2025) - 2024
- [c8]Nicolas Bohm Agostini
, Jude Haris, Perry Gibson, Malith Jayaweera, Norm Rubin, Antonino Tumeo, José L. Abellán, José Cano, David R. Kaeli:
AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators. CGO 2024: 143-157 - 2023
- [j1]Jude Haris
SECDA-TFLite: A toolkit for efficient development of FPGA-based DNN accelerators for edge inference. J. Parallel Distributed Comput. 173: 140-151 (2023) - [c7]Nikolaos Louloudakis, Perry Gibson, José Cano, Ajitha Rajan:
DeltaNN: Assessing the Impact of Computational Environment Parameters on the Performance of Image Recognition Models. ICSME 2023: 414-424 - [c6]Nikolaos Louloudakis, Perry Gibson, José Cano, Ajitha Rajan:
Fault Localization for Buggy Deep Learning Framework Conversions in Image Recognition. ASE 2023: 1795-1799 - [i13]Nikolaos Louloudakis, Perry Gibson, José Cano, Ajitha Rajan:
MutateNN: Mutation Testing of Image Recognition Models Deployed on Hardware Accelerators. CoRR abs/2306.01697 (2023) - [i12]Nikolaos Louloudakis, Perry Gibson, José Cano, Ajitha Rajan:
Fault Localization for Framework Conversions of Image Recognition Models. CoRR abs/2306.06157 (2023) - [i11]Nikolaos Louloudakis, Perry Gibson, José Cano, Ajitha Rajan:
A Differential Testing Framework to Evaluate Image Recognition Model Robustness. CoRR abs/2306.06208 (2023) - [i10]Perry Gibson, José Cano, Elliot J. Crowley, Amos J. Storkey, Michael F. P. O'Boyle:
DLAS: An Exploration and Assessment of the Deep Learning Acceleration Stack. CoRR abs/2311.08909 (2023) - [i9]Nicolas Bohm Agostini, Jude Haris, Perry Gibson, Malith Jayaweera, Norm Rubin, Antonino Tumeo, José L. Abellán, José Cano, David R. Kaeli:
AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators. CoRR abs/2312.14821 (2023) - [i8]Nikolaos Louloudakis, Perry Gibson, José Cano, Ajitha Rajan:
Fix-Con: Automatic Fault Localization and Repair of Deep Learning Model Conversions. CoRR abs/2312.15101 (2023) - 2022
- [c5]Perry Gibson
Transfer-Tuning: Reusing Auto-Schedules for Efficient Tensor Program Code Generation. PACT 2022: 28-39 - [c4]Axel Stjerngren, Perry Gibson
Bifrost: End-to-End Evaluation and optimization of Reconfigurable DNN Accelerators. ISPASS 2022: 288-299 - [i7]Perry Gibson, José Cano:
Reusing Auto-Schedules for Efficient DNN Compilation. CoRR abs/2201.05587 (2022) - [i6]Axel Stjerngren, Perry Gibson, José Cano:
Bifrost: End-to-End Evaluation and Optimization of Reconfigurable DNN Accelerators. CoRR abs/2204.12418 (2022) - [i5]Perry Gibson, José Cano:
Productive Reproducible Workflows for DNNs: A Case Study for Industrial Defect Detection. CoRR abs/2206.09359 (2022) - [i4]Nikolaos Louloudakis, Perry Gibson, José Cano, Ajitha Rajan:
Exploring Effects of Computational Parameter Changes to Image Recognition Systems. CoRR abs/2211.00471 (2022) - 2021
- [c3]Jude Haris
SECDA: Efficient Hardware/Software Co-Design of FPGA-based DNN Accelerators for Edge Inference. SBAC-PAD 2021: 33-43 - [i3]Jude Haris, Perry Gibson, José Cano, Nicolas Bohm Agostini, David R. Kaeli:
SECDA: Efficient Hardware/Software Co-Design of FPGA-based DNN Accelerators for Edge Inference. CoRR abs/2110.00478 (2021) - 2020
- [c2]Perry Gibson
Optimizing Grouped Convolutions on Edge Devices. ASAP 2020: 189-196 - [c1]Perry Gibson
Orpheus: A New Deep Learning Framework for Easy Deployment and Evaluation of Edge Inference. ISPASS 2020: 229-230 - [i2]Perry Gibson, José Cano, Jack Turner, Elliot J. Crowley, Michael F. P. O'Boyle, Amos J. Storkey:
Optimizing Grouped Convolutions on Edge Devices. CoRR abs/2006.09791 (2020) - [i1]Perry Gibson, José Cano:
Orpheus: A New Deep Learning Framework for Easy Deployment and Evaluation of Edge Inference. CoRR abs/2007.13648 (2020)
Coauthor Index
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