Mohamed S. Abdelfattah

According to our database, Mohamed S. Abdelfattah authored at least 51 papers between 2012 and 2024.

Collaborative distances:

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

2024

NITRO: LLM Inference on Intel Laptop NPUs.

Anthony Fei, Mohamed S. Abdelfattah

CoRR, 2024

Attamba: Attending To Multi-Token States.

Yash Akhauri, Safeen Huda, Mohamed S. Abdelfattah

CoRR, 2024

BitMoD: Bit-serial Mixture-of-Datatype LLM Acceleration.

Yuzong Chen, Ahmed F. AbouElhamayed, Xilai Dai, Yang Wang, Marta Andronic, George A. Constantinides, Mohamed S. Abdelfattah

CoRR, 2024

Radial Networks: Dynamic Layer Routing for High-Performance Large Language Models.

Jordan Dotzel, Yash Akhauri, Ahmed S. AbouElhamayed, Carly Jiang, Mohamed S. Abdelfattah, Zhiru Zhang

CoRR, 2024

Fast Inference Through The Reuse Of Attention Maps In Diffusion Models.

Rosco Hunter, Lukasz Dudziak, Mohamed S. Abdelfattah, Abhinav Mehrotra, Sourav Bhattacharya, Hongkai Wen

CoRR, 2024

On Latency Predictors for Neural Architecture Search.

Yash Akhauri, Mohamed S. Abdelfattah

Proceedings of the Seventh Annual Conference on Machine Learning and Systems, 2024

BBS: Bi-Directional Bit-Level Sparsity for Deep Learning Acceleration.

Yuzong Chen, Jian Meng, Jae-sun Seo, Mohamed S. Abdelfattah

Proceedings of the 57th IEEE/ACM International Symposium on Microarchitecture, 2024

Towards Neural Architecture Search through Hierarchical Generative Modeling.

Lichuan Xiang, Lukasz Dudziak, Mohamed S. Abdelfattah, Abhinav Mehrotra, Nicholas Donald Lane, Hongkai Wen

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning from Students: Applying t-Distributions to Explore Accurate and Efficient Formats for LLMs.

Jordan Dotzel, Yuzong Chen, Bahaa Kotb, Sushma Prasad, Gang Wu, Sheng Li, Mohamed S. Abdelfattah, Zhiru Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Encodings for Prediction-based Neural Architecture Search.

Yash Akhauri, Mohamed S. Abdelfattah

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Exploring the Limits of Semantic Image Compression at Micro-bits per Pixel.

Jordan Dotzel, Bahaa Kotb, James Dotzel, Mohamed S. Abdelfattah, Zhiru Zhang

Proceedings of the Second Tiny Papers Track at ICLR 2024, 2024

Kratos: An FPGA Benchmark for Unrolled DNNs with Fine-Grained Sparsity and Mixed Precision.

Xilai Dai, Yuzong Chen, Mohamed S. Abdelfattah

Proceedings of the 34th International Conference on Field-Programmable Logic and Applications, 2024

FPGA Benchmark for Unrolled DNNs with Fine-Grained Sparsity and Mixed Precision.

Xilai Dai, Yuzong Chen, Mohamed S. Abdelfattah

Proceedings of the 32nd IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2024

ShadowLLM: Predictor-based Contextual Sparsity for Large Language Models.

Yash Akhauri, Ahmed F. AbouElhamayed, Jordan Dotzel, Zhiru Zhang, Alexander M. Rush, Safeen Huda, Mohamed S. Abdelfattah

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Beyond Inference: Performance Analysis of DNN Server Overheads for Computer Vision.

Ahmed F. AbouElhamayed, Susanne Balle, Deshanand P. Singh, Mohamed S. Abdelfattah

Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

2023

Logic Shrinkage: Learned Connectivity Sparsification for LUT-Based Neural Networks.

Erwei Wang, Marie Auffret, Georgios-Ilias Stavrou, Peter Y. K. Cheung, George A. Constantinides, Mohamed S. Abdelfattah, James J. Davis

ACM Trans. Reconfigurable Technol. Syst., December, 2023

FLIQS: One-Shot Mixed-Precision Floating-Point and Integer Quantization Search.

Jordan Dotzel, Gang Wu, Andrew Li, Muhammad Umar, Yun Ni, Mohamed S. Abdelfattah, Zhiru Zhang, Liqun Cheng, Martin G. Dixon, Norman P. Jouppi, Quoc V. Le, Sheng Li

CoRR, 2023

Are We There Yet? Product Quantization and its Hardware Acceleration.

Javier Fernández-Marqués, Ahmed F. AbouElhamayed, Nicholas D. Lane, Mohamed S. Abdelfattah

CoRR, 2023

DiviML: A Module-based Heuristic for Mapping Neural Networks onto Heterogeneous Platforms.

Yassine Ghannane, Mohamed S. Abdelfattah

Proceedings of the IEEE/ACM International Conference on Computer Aided Design, 2023

M4BRAM: Mixed-Precision Matrix-Matrix Multiplication in FPGA Block RAMs.

Yuzong Chen, Jordan Dotzel, Mohamed S. Abdelfattah

Proceedings of the International Conference on Field Programmable Technology, 2023

BRAMAC: Compute-in-BRAM Architectures for Multiply-Accumulate on FPGAs.

Yuzong Chen, Mohamed S. Abdelfattah

Proceedings of the 31st IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2023

Multi-Predict: Few Shot Predictors For Efficient Neural Architecture Search.

Yash Akhauri, Mohamed S. Abdelfattah

Proceedings of the International Conference on Automated Machine Learning, 2023

Zero-Cost Operation Scoring in Differentiable Architecture Search.

Lichuan Xiang, Lukasz Dudziak, Mohamed S. Abdelfattah, Thomas C. P. Chau, Nicholas D. Lane, Hongkai Wen

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

BLOX: Macro Neural Architecture Search Benchmark and Algorithms.

Thomas Chau, Lukasz Dudziak, Hongkai Wen, Nicholas D. Lane, Mohamed S. Abdelfattah

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Adaptable Butterfly Accelerator for Attention-based NNs via Hardware and Algorithm Co-design.

Hongxiang Fan, Thomas Chau, Stylianos I. Venieris, Royson Lee, Alexandros Kouris, Wayne Luk, Nicholas D. Lane, Mohamed S. Abdelfattah

Proceedings of the 55th IEEE/ACM International Symposium on Microarchitecture, 2022

Logic Shrinkage: Learned FPGA Netlist Sparsity for Efficient Neural Network Inference.

Erwei Wang, James J. Davis, Georgios-Ilias Stavrou, Peter Y. K. Cheung, George A. Constantinides, Mohamed S. Abdelfattah

Proceedings of the FPGA '22: The 2022 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, Virtual Event, USA, 27 February 2022, 2022

2021

Zero-Cost Proxies Meet Differentiable Architecture Search.

Lichuan Xiang, Lukasz Dudziak, Mohamed S. Abdelfattah, Thomas Chau, Nicholas D. Lane, Hongkai Wen

CoRR, 2021

Are Mobile DNN Accelerators Accelerating DNNs?

Qingqing Cao, Alexandru Eugen Irimiea, Mohamed S. Abdelfattah, Aruna Balasubramanian, Nicholas D. Lane

Proceedings of the EMDL@MobiSys 2021: Proceedings of the 5th International Workshop on Embedded and Mobile Deep Learning, 2021

NAS-Bench-ASR: Reproducible Neural Architecture Search for Speech Recognition.

Abhinav Mehrotra, Alberto Gil C. P. Ramos, Sourav Bhattacharya, Lukasz Dudziak, Ravichander Vipperla, Thomas Chau, Mohamed S. Abdelfattah, Samin Ishtiaq, Nicholas Donald Lane

Proceedings of the 9th International Conference on Learning Representations, 2021

Zero-Cost Proxies for Lightweight NAS.

Mohamed S. Abdelfattah, Abhinav Mehrotra, Lukasz Dudziak, Nicholas Donald Lane

Proceedings of the 9th International Conference on Learning Representations, 2021

Temporal Kernel Consistency for Blind Video Super-Resolution.

Lichuan Xiang, Royson Lee, Mohamed S. Abdelfattah, Nicholas D. Lane, Hongkai Wen

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

2020

BRP-NAS: Prediction-based NAS using GCNs.

Lukasz Dudziak, Thomas Chau, Mohamed S. Abdelfattah, Royson Lee, Hyeji Kim, Nicholas D. Lane

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Iterative Compression of End-to-End ASR Model Using AutoML.

Abhinav Mehrotra, Lukasz Dudziak, Jinsu Yeo, Young-Yoon Lee, Ravichander Vipperla, Mohamed S. Abdelfattah, Sourav Bhattacharya, Samin Ishtiaq, Alberto Gil C. P. Ramos, SangJeong Lee, Daehyun Kim, Nicholas D. Lane

Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

Codesign-NAS: Automatic FPGA/CNN Codesign Using Neural Architecture Search.

Mohamed S. Abdelfattah, Lukasz Dudziak, Thomas Chau, Royson Lee, Hyeji Kim, Nicholas D. Lane

Proceedings of the FPGA '20: The 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2020

Journey Towards Tiny Perceptual Super-Resolution.

Royson Lee, Lukasz Dudziak, Mohamed S. Abdelfattah, Stylianos I. Venieris, Hyeji Kim, Hongkai Wen, Nicholas D. Lane

Proceedings of the Computer Vision - ECCV 2020, 2020

Best of Both Worlds: AutoML Codesign of a CNN and its Hardware Accelerator.

Mohamed S. Abdelfattah, Lukasz Dudziak, Thomas Chau, Royson Lee, Hyeji Kim, Nicholas D. Lane

Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020

2019

ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning.

Lukasz Dudziak, Mohamed S. Abdelfattah, Ravichander Vipperla, Stefanos Laskaridis, Nicholas D. Lane

Proceedings of the 20th Annual Conference of the International Speech Communication Association, 2019

2018

Flexibility: FPGAs and CAD in Deep Learning Acceleration.

Gordon R. Chiu, Andrew C. Ling, Davor Capalija, Andrew Bitar, Mohamed S. Abdelfattah

Proceedings of the 2018 International Symposium on Physical Design, 2018

Harnessing Numerical Flexibility for Deep Learning on FPGAs.

Andrew C. Ling, Mohamed S. Abdelfattah, Shane O'Connell, Andrew Bitar, David Han, Roberto DiCecco, Suchit Subhaschandra, Chris N. Johnson, Dmitry Denisenko, Joshua Fender, Gordon R. Chiu

Proceedings of the 9th International Symposium on Highly-Efficient Accelerators and Reconfigurable Technologies, 2018

DLA: Compiler and FPGA Overlay for Neural Network Inference Acceleration.

Mohamed S. Abdelfattah, David Han, Andrew Bitar, Roberto DiCecco, Shane O'Connell, Nitika Shanker, Joseph Chu, Ian Prins, Joshua Fender, Andrew C. Ling, Gordon R. Chiu

Proceedings of the 28th International Conference on Field Programmable Logic and Applications, 2018

2017

Design and Applications for Embedded Networks-on-Chip on FPGAs.

Mohamed S. Abdelfattah, Andrew Bitar, Vaughn Betz

IEEE Trans. Computers, 2017

2016

Power Analysis of Embedded NoCs on FPGAs and Comparison With Custom Buses.

Mohamed S. Abdelfattah, Vaughn Betz

IEEE Trans. Very Large Scale Integr. Syst., 2016

LYNX: CAD for FPGA-based networks-on-chip.

Mohamed S. Abdelfattah, Vaughn Betz

Proceedings of the 26th International Conference on Field Programmable Logic and Applications, 2016

2015

Bringing programmability to the data plane: Packet processing with a NoC-enhanced FPGA.

Andrew Bitar, Mohamed S. Abdelfattah, Vaughn Betz

Proceedings of the 2015 International Conference on Field Programmable Technology, 2015

Design and simulation tools for Embedded NOCs on FPGAs.

Mohamed S. Abdelfattah, Andrew Bitar, Ange Yaghi, Vaughn Betz

Proceedings of the 25th International Conference on Field Programmable Logic and Applications, 2015

Take the Highway: Design for Embedded NoCs on FPGAs.

Mohamed S. Abdelfattah, Andrew Bitar, Vaughn Betz

Proceedings of the 2015 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2015

2014

Networks-on-Chip for FPGAs: Hard, Soft or Mixed?

Mohamed S. Abdelfattah, Vaughn Betz

ACM Trans. Reconfigurable Technol. Syst., 2014

The Case for Embedded Networks on Chip on Field-Programmable Gate Arrays.

Mohamed S. Abdelfattah, Vaughn Betz

IEEE Micro, 2014

Gzip on a chip: high performance lossless data compression on FPGAs using OpenCL.

Mohamed S. Abdelfattah, Andrei Hagiescu, Deshanand P. Singh

Proceedings of the International Workshop on OpenCL, 2014

2013

The power of communication: Energy-efficient NOCS for FPGAS.

Mohamed S. Abdelfattah, Vaughn Betz

Proceedings of the 23rd International Conference on Field programmable Logic and Applications, 2013

2012

Design tradeoffs for hard and soft FPGA-based Networks-on-Chip.

Mohamed S. Abdelfattah, Vaughn Betz

Proceedings of the 2012 International Conference on Field-Programmable Technology, 2012