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Ali Hadi Zadeh
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2020 – today
- 2024
- [c7]Alberto Delmas Lascorz, Mostafa Mahmoud, Ali Hadi Zadeh, Milos Nikolic, Kareem Ibrahim, Christina Giannoula, Ameer Abdelhadi, Andreas Moshovos:
Atalanta: A Bit is Worth a "Thousand" Tensor Values. ASPLOS (2) 2024: 85-102 - [c6]Milos Nikolic, Enrique Torres-Sánchez, Jiahui Wang, Ali Hadi Zadeh, Mostafa Mahmoud, Ameer Abdelhadi, Kareem Ibrahim, Andreas Moshovos:
Schrodinger's FP Training Neural Networks with Dynamic Floating-Point Containers. MLSys 2024 - 2022
- [c5]Ali Hadi Zadeh, Mostafa Mahmoud, Ameer Abdelhadi, Andreas Moshovos:
Mokey: enabling narrow fixed-point inference for out-of-the-box floating-point transformer models. ISCA 2022: 888-901 - [i5]Ali Hadi Zadeh, Mostafa Mahmoud, Ameer Abdelhadi, Andreas Moshovos:
Mokey: Enabling Narrow Fixed-Point Inference for Out-of-the-Box Floating-Point Transformer Models. CoRR abs/2203.12758 (2022) - [i4]Milos Nikolic, Enrique Torres-Sánchez, Jiahui Wang, Ali Hadi Zadeh, Mostafa Mahmoud, Ameer Abdelhadi, Andreas Moshovos:
Schrödinger's FP: Dynamic Adaptation of Floating-Point Containers for Deep Learning Training. CoRR abs/2204.13666 (2022) - 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 - [i3]Ali Hadi Zadeh, Andreas Moshovos:
GOBO: Quantizing Attention-Based NLP Models for Low Latency and Energy Efficient Inference. CoRR abs/2005.03842 (2020) - [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]Ali Hadi Zadeh, Matin Hashemi, Mohammad Labbaf, Mostafa Parniani:
A Matrix-Inversion Technique for FPGA-Based Real-Time EMT Simulation of Power Converters. IEEE Trans. Ind. Electron. 66(2): 1224-1234 (2019) - [c1]Ali Hadi Zadeh, Zissis Poulos, Andreas Moshovos:
Deep Learning Language Modeling Workloads: Where Time Goes on Graphics Processors. IISWC 2019: 131-142
Coauthor Index
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last updated on 2024-07-02 21:28 CEST by the dblp team
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