2023

  • J. Haris, P. Gibson, J. Cano, N. Bohm Agostini, D. Kaeli, ‘SECDA-TFLite: A Toolkit for Efficient Development of FPGA-based DNN Accelerators for Edge Inference’, (to appear) in Elsevier Journal of Parallel and Distributed Computing (JPDC), Volume 173, March 2023. [Paper] [Code]

2022

  • N. Louloudakis, P. Gibson, J. Cano, A. Rajan, ‘Assessing Robustness of Image Recognition Models to Changes in the Computational Environment’, (to appear) in NeurIPS ML Safety Workshop (MLSW) co-located with NeurIPS, Hybrid Conference, November-December 2022. [Pre-print]

  • P. Gibson, J. Cano, ‘Transfer-Tuning: Reusing Auto-Schedules for Efficient Tensor Program Code Generation’, in 31st International Conference on Parallel Architectures and Compilation Techniques (PACT), Chicago, USA, October 2022. [Paper] [arXiv] [Code artifact]

  • A. Stjerngren, P. Gibson, J. Cano, ‘Bifrost: End-to-End Evaluation and Optimization of Reconfigurable DNN Accelerators’, in IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), Singapore, May 2022. [Paper] [arXiv] [Code]

  • P. Gibson, J. Cano, ‘Productive Reproducible Workflows for DNNs: A Case Study for Industrial Defect Detection’, in 4th Workshop on Accelerated Machine Learning (AccML) co-located with HiPEAC, Budapest, Hungary, June 2022. [Paper]

2021

  • S. Dong, Y. Sun, N. Bohm Agostini, E. Karimi, D. Lowell, J. Zhou, J. Cano, J. L. Abellán, D. Kaeli, ‘Spartan: A Sparsity-Adaptive Framework to Accelerate Deep Neural Network Training on GPUs’, in IEEE Transactions on Parallel and Distributed Systems (TPDS), Volume 32, Issue 10, October 2021. [Paper]

  • J. Haris, P. Gibson, J. Cano, N. B. Agostini, and D. Kaeli, ‘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, October 2021. [Paper] [arXiv] [Code]

  • M. Lofqvist, J. Cano, ‘Optimizing Data Processing in Space for Object Detection in Satellite Imagery’, in 35th Annual Small Satellite Conference (SmallSat), Virtual Event, August 2021. [Paper] [arXiv]

2020

  • N. Bohm Agostini, S. Dong, E. Karimi, M. Torrents, J. Cano, J. L. Abellán, D. Kaeli, ‘Design Space Exploration of Accelerators and End-to-End DNN Evaluation with TFLITE-SOC’, in 32nd IEEE International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), Porto, Portugal, September 2020. [Paper]

  • P. Gibson and J. Cano, ‘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), Virtual Meeting, August 2020. [Paper] [arXiv]

  • M. Lofqvist, J. Cano, ‘Accelerating Deep Learning Applications in Space’, in 34th Annual Small Satellite Conference (SmallSat), Virtual Event, August 2020. [Paper] [arXiv]

  • P. Gibson, J. Cano, J. Turner, E. J. Crowley, M. O’Boyle, and A. Storkey, ‘Optimizing grouped convolutions on edge devices’, in 2020 IEEE 31st international conference on application-specific systems, architectures and processors (ASAP), Manchester, UK, July 2020. [Paper] [arXiv] [Code]