Omar Mohamed Awad

According to our database, Omar Mohamed Awad authored at least 12 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

SkipViT: Speeding Up Vision Transformers with a Token-Level Skip Connection.

Foozhan Ataiefard, Walid Ahmed, Habib Hajimolahoseini, Saina Asani, Farnoosh Javadi, Mohammad Hassanpour, Omar Mohamed Awad, Austin Wen, Kangling Liu, Yang Liu

CoRR, 2024

BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization.

Milos Nikolic, Ghouthi Boukli Hacene, Ciaran Bannon, Alberto Delmas Lascorz, Matthieu Courbariaux, Omar Mohamed Awad, Isak Edo Vivancos, Yoshua Bengio, Vincent Gripon, Andreas Moshovos

Proceedings of the IEEE International Symposium on Circuits and Systems, 2024

2023

SwiftLearn: A Data-Efficient Training Method of Deep Learning Models using Importance Sampling.

Habib Hajimolahoseini, Omar Mohamed Awad, Walid Ahmed, Austin Wen, Saina Asani, Mohammad Hassanpour, Farnoosh Javadi, Mehdi Ahmadi, Foozhan Ataiefard, Kangling Liu, Yang Liu

CoRR, 2023

GQKVA: Efficient Pre-training of Transformers by Grouping Queries, Keys, and Values.

Farnoosh Javadi, Walid Ahmed, Habib Hajimolahoseini, Foozhan Ataiefard, Mohammad Hassanpour, Saina Asani, Austin Wen, Omar Mohamed Awad, Kangling Liu, Yang Liu

CoRR, 2023

Improving Resnet-9 Generalization Trained on Small Datasets.

Omar Mohamed Awad, Habib Hajimolahoseini, Michael Lim, Gurpreet Gosal, Walid Ahmed, Yang Liu, Gordon Deng

CoRR, 2023

cuSCNN : an Efficient CUDA Implementation of Sparse CNNs.

Mohamed A. Elgammal, Omar Mohamed Awad, Isak Edo Vivancos, Andreas Moshovos, Vaughn Betz

Proceedings of the 13th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies, 2023

2021

FPRaker: A Processing Element For Accelerating Neural Network Training.

Omar Mohamed Awad, Mostafa Mahmoud, Isak Edo, Ali Hadi Zadeh, Ciaran Bannon, Anand Jayarajan, Gennady Pekhimenko, Andreas Moshovos

Proceedings of the MICRO '21: 54th Annual IEEE/ACM International Symposium on Microarchitecture, 2021

2020

TensorDash: Exploiting Sparsity to Accelerate Deep Neural Network Training and Inference.

Mostafa Mahmoud, Isak Edo Vivancos, Ali Hadi Zadeh, Omar Mohamed Awad, Gennady Pekhimenko, Jorge Albericio, Andreas Moshovos

CoRR, 2020

GOBO: Quantizing Attention-Based NLP Models for Low Latency and Energy Efficient Inference.

Ali Hadi Zadeh, Isak Edo, Omar Mohamed Awad, Andreas Moshovos

Proceedings of the 53rd Annual IEEE/ACM International Symposium on Microarchitecture, 2020

TensorDash: Exploiting Sparsity to Accelerate Deep Neural Network Training.

Mostafa Mahmoud, Isak Edo, Ali Hadi Zadeh, Omar Mohamed Awad, Gennady Pekhimenko, Jorge Albericio, Andreas Moshovos

Proceedings of the 53rd Annual IEEE/ACM International Symposium on Microarchitecture, 2020

2019

Security Implications of Intentional Capacitive Crosstalk.

Christian Kison, Omar Mohamed Awad, Marc Fyrbiak, Christof Paar

IEEE Trans. Inf. Forensics Secur., 2019

ShapeShifter: Enabling Fine-Grain Data Width Adaptation in Deep Learning.

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

Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture, 2019