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Omar Mohamed Awad
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2020 – today
- 2024
- [c6]Milos Nikolic, Ghouthi Boukli Hacene, Ciaran Bannon, Alberto Delmas Lascorz, Matthieu Courbariaux, Omar Mohamed Awad, Isak Edo Vivancos, Yoshua Bengio, Vincent Gripon, Andreas Moshovos:
BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization. ISCAS 2024: 1-5 - [i6]Foozhan Ataiefard, Walid Ahmed, Habib Hajimolahoseini, Saina Asani, Farnoosh Javadi, Mohammad Hassanpour, Omar Mohamed Awad, Austin Wen, Kangling Liu, Yang Liu:
SkipViT: Speeding Up Vision Transformers with a Token-Level Skip Connection. CoRR abs/2401.15293 (2024) - 2023
- [c5]Mohamed A. Elgammal, Omar Mohamed Awad, Isak Edo Vivancos, Andreas Moshovos, Vaughn Betz:
cuSCNN : an Efficient CUDA Implementation of Sparse CNNs. HEART 2023: 107-113 - [i5]Omar Mohamed Awad, Habib Hajimolahoseini, Michael Lim, Gurpreet Gosal, Walid Ahmed, Yang Liu, Gordon Deng:
Improving Resnet-9 Generalization Trained on Small Datasets. CoRR abs/2309.03965 (2023) - [i4]Farnoosh Javadi, Walid Ahmed, Habib Hajimolahoseini, Foozhan Ataiefard, Mohammad Hassanpour, Saina Asani, Austin Wen, Omar Mohamed Awad, Kangling Liu, Yang Liu:
GQKVA: Efficient Pre-training of Transformers by Grouping Queries, Keys, and Values. CoRR abs/2311.03426 (2023) - [i3]Habib Hajimolahoseini, Omar Mohamed Awad, Walid Ahmed, Austin Wen, Saina Asani, Mohammad Hassanpour, Farnoosh Javadi, Mehdi Ahmadi, Foozhan Ataiefard, Kangling Liu, Yang Liu:
SwiftLearn: A Data-Efficient Training Method of Deep Learning Models using Importance Sampling. CoRR abs/2311.15134 (2023) - 2021
- [c4]Omar Mohamed Awad, Mostafa Mahmoud, Isak Edo, Ali Hadi Zadeh, Ciaran Bannon, Anand Jayarajan, Gennady Pekhimenko, Andreas Moshovos:
FPRaker: A Processing Element For Accelerating Neural Network Training. MICRO 2021: 857-869 - 2020
- [c3]Mostafa Mahmoud, Isak Edo, Ali Hadi Zadeh, Omar Mohamed Awad, Gennady Pekhimenko, Jorge Albericio, Andreas Moshovos:
TensorDash: Exploiting Sparsity to Accelerate Deep Neural Network Training. MICRO 2020: 781-795 - [c2]Ali Hadi Zadeh, Isak Edo, Omar Mohamed Awad, Andreas Moshovos:
GOBO: Quantizing Attention-Based NLP Models for Low Latency and Energy Efficient Inference. MICRO 2020: 811-824 - [i2]Mostafa Mahmoud, Isak Edo Vivancos, Ali Hadi Zadeh, Omar Mohamed Awad, Gennady Pekhimenko, Jorge Albericio, Andreas Moshovos:
TensorDash: Exploiting Sparsity to Accelerate Deep Neural Network Training and Inference. CoRR abs/2009.00748 (2020) - [i1]Omar Mohamed Awad, Mostafa Mahmoud, Isak Edo Vivancos, Ali Hadi Zadeh, Ciaran Bannon, Anand Jayarajan, Gennady Pekhimenko, Andreas Moshovos:
FPRaker: A Processing Element For Accelerating Neural Network Training. CoRR abs/2010.08065 (2020)
2010 – 2019
- 2019
- [j1]Christian Kison, Omar Mohamed Awad, Marc Fyrbiak, Christof Paar:
Security Implications of Intentional Capacitive Crosstalk. IEEE Trans. Inf. Forensics Secur. 14(12): 3246-3258 (2019) - [c1]Alberto Delmas Lascorz, Sayeh Sharify, Isak Edo Vivancos, Dylan Malone Stuart, Omar Mohamed Awad, Patrick Judd, Mostafa Mahmoud, Milos Nikolic, Kevin Siu, Zissis Poulos, Andreas Moshovos:
ShapeShifter: Enabling Fine-Grain Data Width Adaptation in Deep Learning. MICRO 2019: 28-41
Coauthor Index
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last updated on 2024-07-17 20:34 CEST by the dblp team
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