 | Up a level |
AskariHemmat, M.H., Dupuis, T., Fournier, Y., El Zarif, N., Cavalcante, M., Perotti, M., Gurkaynak, F., Benini, L., Leduc-Primeau, F., Savaria, Y., & David, J. P. Quark: an integer RISC-V vector processor for sub-byte quantized DNN inference [Paper]. 2023 IEEE International Symposium on Circuits and Systems (ISCAS 2023), Monterey, CA, USA (5 pages). External link
AskariHemmat, M.H., Bilaniuk, O., Wagner, S., Savaria, Y., & David, J. P. (2021, May). RISC-V barrel processor for deep neural network acceleration [Paper]. 53rd IEEE International Symposium on Circuits and Systems (ISCAS 2021), Daegu, Korea (5 pages). External link
AskariHemmat, M.H., Honari, S., Rouhier, L., Perone, C. S., Cohen-Adad, J., Savaria, Y., & David, J. P. (2019, October). U-net fixed-point quantization for medical image segmentation [Paper]. 1st International Workshop on Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention (HAL-MICCAI 2019), Shenzhen, China. External link
Dupuis, T., Fournier, Y., AskariHemmat, M.H., Zarif, N. E., Leduc-Primeau, F., David, J. P., & Savaria, Y. (2023, June). Sparq: A Custom RISC-V Vector Processor for Efficient Sub-Byte Quantized Inference [Paper]. 21st IEEE Interregional NEWCAS Conference (NEWCAS 2023), Edinburgh, United Kingdom (5 pages). External link
Sankaran, A., Mastropietro, O., Saboori, E., Idris, Y., Sawyer, D., AskariHemmat, M.H., & Hacene, G. B. (2021, February). Deeplite Neutrino (TM): An End-to-End Framework for Constrained Deep Learning Model Optimization [Paper]. 35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence. External link
