Up a level |
Ahmadi, M., Vakili, S., & Langlois, J. M. P. (2021). CARLA: A Convolution Accelerator with a Reconfigurable and Low-Energy Architecture. IEEE Transactions on Circuits and Systems I: Regular Papers, 68(8), 3184-3196. External link
Ahmadi, M. (2020). Energy-Efficient, Flexible and Fast Architectures for Deep Convolutional Neural Network Acceleration [Ph.D. thesis, Polytechnique Montréal]. Available
Ahmadi, M., Vakili, S., & Langlois, J. M. P. (2020, June). An energy-efficient accelerator architecture with serial accumulation dataflow for deep CNNs [Paper]. 18th IEEE International New Circuits and Systems Conference (NEWCAS 2020), Montréal, Québec. External link
Ahmadi, M., Vakili, S., & Langlois, J. M. P. (2020, June). Heterogeneous distributed SRAM configuration for energy-efficient deep CNN accelerators [Paper]. 18th IEEE International New Circuits and Systems Conference (NEWCAS 2020), Montréal, Québec. External link
Ardakani, A., Condo, C., Ahmadi, M., & Gross, W. J. (2018). An architecture to accelerate convolution in deep neural networks. IEEE Transactions on Circuits and Systems I: Regular Papers, 65(4), 1349-1362. External link
Ahmadi, M., Vakili, S., Langlois, J. M. P., & Gross, W. J. (2018, June). Power Reduction in CNN Pooling Layers with a Preliminary Partial Computation Strategy [Paper]. 16th IEEE International New Circuits and Systems Conference (NEWCAS 2018), Montréal, Québec. External link