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), 2023. [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. [Pre-print], [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), 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), October 2021, pp. 33–43. [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, pp. 229–230. [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, pp. 189–196. [Paper], [arXiv], [Code].