Perry Gibson
Research title: Modular development of across-stack deep learning inference accelerators on heterogeneous devices
Publications
2022
Stjerngren, A., Gibson, P. and Cano, J. (2022) Bifrost: End-to-End Evaluation and optimization of Reconfigurable DNN Accelerators. In: 2022 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), Singapore, 22-24 May 2022, pp. 288-299. ISBN 9781665459549 (doi: 10.1109/ISPASS55109.2022.00042)
2021
Haris, J., Gibson, P. , Cano, J. , Bohm Agostini, N. and Kaeli, D. (2021) SECDA: Efficient Hardware/Software Co-design of FPGA-based DNN Accelerators for Edge Inference. In: 2021 IEEE 33rd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), Belo Horizonte, Brazil, 26-28 Oct 2021, (In Press)
2020
Gibson, P. and Cano, J. (2020) Orpheus: a New Deep Learning Framework for Easy Deployment and Evaluation of Edge Inference. In: 2020 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), 23-26 Aug 2020, pp. 229-230. ISBN 9781728147987 (doi: 10.1109/ISPASS48437.2020.00042)
Gibson, P. , Cano, J. , Turner, J., Crowley, E. J., O’Boyle, M. and Storkey, A. (2020) Evaluating Grouped Spatial Pack Convolutions on Edge CPUs. 16th International Summer School on Advanced Computer Architecture and Compilation for High-Performance and Embedded Systems (ACACES), Online, 06-17 Jul 2020.
Gibson, P. , Cano, J. , Turner, J., Crowley, E. J., O’Boyle, M. and Storkey, A. (2020) Optimizing Grouped Convolutions on Edge Devices. In: 2020 IEEE 31st International Conference on Application-specific Systems, Architectures and Processors (ASAP), Manchester, UK, 06-08 Jul 2020, pp. 189-196. ISBN 9781728171470 (doi: 10.1109/ASAP49362.2020.00039)
Conference or Workshop Item
Gibson, P. , Cano, J. , Turner, J., Crowley, E. J., O’Boyle, M. and Storkey, A. (2020) Evaluating Grouped Spatial Pack Convolutions on Edge CPUs. 16th International Summer School on Advanced Computer Architecture and Compilation for High-Performance and Embedded Systems (ACACES), Online, 06-17 Jul 2020.
Conference Proceedings
Stjerngren, A., Gibson, P. and Cano, J. (2022) Bifrost: End-to-End Evaluation and optimization of Reconfigurable DNN Accelerators. In: 2022 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), Singapore, 22-24 May 2022, pp. 288-299. ISBN 9781665459549 (doi: 10.1109/ISPASS55109.2022.00042)
Haris, J., Gibson, P. , Cano, J. , Bohm Agostini, N. and Kaeli, D. (2021) SECDA: Efficient Hardware/Software Co-design of FPGA-based DNN Accelerators for Edge Inference. In: 2021 IEEE 33rd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), Belo Horizonte, Brazil, 26-28 Oct 2021, (In Press)
Gibson, P. and Cano, J. (2020) Orpheus: a New Deep Learning Framework for Easy Deployment and Evaluation of Edge Inference. In: 2020 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), 23-26 Aug 2020, pp. 229-230. ISBN 9781728147987 (doi: 10.1109/ISPASS48437.2020.00042)
Gibson, P. , Cano, J. , Turner, J., Crowley, E. J., O’Boyle, M. and Storkey, A. (2020) Optimizing Grouped Convolutions on Edge Devices. In: 2020 IEEE 31st International Conference on Application-specific Systems, Architectures and Processors (ASAP), Manchester, UK, 06-08 Jul 2020, pp. 189-196. ISBN 9781728171470 (doi: 10.1109/ASAP49362.2020.00039)