Taha Soliman

Orcid: 0000-0002-9421-9489

According to our database1, Taha Soliman authored at least 16 papers between 2019 and 2023.

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Bibliography

2023
Demonstration of Differential Mode Ferroelectric Field-Effect Transistor Array-Based in-Memory Computing Macro for Realizing Multiprecision Mixed-Signal Artificial Intelligence Accelerator.
Adv. Intell. Syst., June, 2023

Torwards Variability Immune Scalable FeFET-based Macros for IMC DNN Accelerators.
Proceedings of the 30th IEEE International Conference on Electronics, Circuits and Systems, 2023

SimPyler: A Compiler-Based Simulation Framework for Machine Learning Accelerators.
Proceedings of the 34th IEEE International Conference on Application-specific Systems, 2023

Simulation-driven Latency Estimations for Multi-core Machine Learning Accelerators.
Proceedings of the 5th IEEE International Conference on Artificial Intelligence Circuits and Systems, 2023

2022
FELIX: A Ferroelectric FET Based Low Power Mixed-Signal In-Memory Architecture for DNN Acceleration.
ACM Trans. Embed. Comput. Syst., November, 2022

Increasing Throughput of In-Memory DNN Accelerators by Flexible Layerwise DNN Approximation.
IEEE Micro, 2022

A Weighted Current Summation Based Mixed Signal DRAM-PIM Architecture for Deep Neural Network Inference.
IEEE J. Emerg. Sel. Topics Circuits Syst., 2022

FeFET versus DRAM based PIM Architectures: A Comparative Study.
Proceedings of the 30th IFIP/IEEE 30th International Conference on Very Large Scale Integration, 2022

Efficient Hardware Approximation for Bit-Decomposition Based Deep Neural Network Accelerators.
Proceedings of the 35th IEEE International System-on-Chip Conference, 2022

2021
Exploiting Resiliency for Kernel-Wise CNN Approximation Enabled by Adaptive Hardware Design.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2021

A Novel DRAM-Based Process-in-Memory Architecture and its Implementation for CNNs.
Proceedings of the ASPDAC '21: 26th Asia and South Pacific Design Automation Conference, 2021

Adaptable Approximation Based on Bit Decomposition for Deep Neural Network Accelerators.
Proceedings of the 3rd IEEE International Conference on Artificial Intelligence Circuits and Systems, 2021

2020
A Ferroelectric FET Based In-memory Architecture for Multi-Precision Neural Networks.
Proceedings of the 33rd IEEE International System-on-Chip Conference, 2020

Enhancing the Utilization of Dot-Product Engines in Deep Learning Accelerators.
Proceedings of the 2020 IEEE International Parallel and Distributed Processing Symposium Workshops, 2020

Efficient FeFET Crossbar Accelerator for Binary Neural Networks.
Proceedings of the 31st IEEE International Conference on Application-specific Systems, 2020

2019
Fast validation of DRAM protocols with timed petri nets.
Proceedings of the International Symposium on Memory Systems, 2019


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