Cecilia De la Parra

According to our database, Cecilia De la Parra authored at least 13 papers between 2020 and 2023.

Collaborative distances:

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

2023

Torwards Variability Immune Scalable FeFET-based Macros for IMC DNN Accelerators.

Nellie Laleni, Taha Soliman, Cecilia De la Parra, Franz Müller, Tobias Kirchner, Andre Guntoro, Thomas Kämpfe, Norbert Wehn, T. Jang

Proceedings of the 30th IEEE International Conference on Electronics, Circuits and Systems, 2023

2022

Increasing Throughput of In-Memory DNN Accelerators by Flexible Layerwise DNN Approximation.

Cecilia De la Parra, Taha Soliman, Andre Guntoro, Akash Kumar, Norbert Wehn

IEEE Micro, 2022

Efficient Hardware Approximation for Bit-Decomposition Based Deep Neural Network Accelerators.

Taha Soliman, Amro Eldebiky, Cecilia De la Parra, Andre Guntoro, Norbert Wehn

Proceedings of the 35th IEEE International System-on-Chip Conference, 2022

2021

Exploiting Resiliency for Kernel-Wise CNN Approximation Enabled by Adaptive Hardware Design.

Cecilia De la Parra, Ahmed El-Yamany, Taha Soliman, Akash Kumar, Norbert Wehn, Andre Guntoro

Proceedings of the IEEE International Symposium on Circuits and Systems, 2021

Knowledge Distillation and Gradient Estimation for Active Error Compensation in Approximate Neural Networks.

Cecilia De la Parra, Xuyi Wu, Andre Guntoro, Akash Kumar

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021

A Novel DRAM-Based Process-in-Memory Architecture and its Implementation for CNNs.

Chirag Sudarshan, Taha Soliman, Cecilia De la Parra, Christian Weis, Leonardo Ecco, Matthias Jung, Norbert Wehn, Andre Guntoro

Proceedings of the ASPDAC '21: 26th Asia and South Pacific Design Automation Conference, 2021

Efficient Accuracy Recovery in Approximate Neural Networks by Systematic Error Modelling.

Cecilia De la Parra, Andre Guntoro, Akash Kumar

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.

Taha Soliman, Cecilia De la Parra, Andre Guntoro, Norbert Wehn

Proceedings of the 3rd IEEE International Conference on Artificial Intelligence Circuits and Systems, 2021

2020

Improving approximate neural networks for perception tasks through specialized optimization.

Cecilia De la Parra, Andre Guntoro, Akash Kumar

Future Gener. Comput. Syst., 2020

Full Approximation of Deep Neural Networks through Efficient Optimization.

Cecilia De la Parra, Andre Guntoro, Akash Kumar

Proceedings of the IEEE International Symposium on Circuits and Systems, 2020

ProxSim: GPU-based Simulation Framework for Cross-Layer Approximate DNN Optimization.

Cecilia De la Parra, Andre Guntoro, Akash Kumar

Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020

Next Generation Arithmetic for Edge Computing.

Andre Guntoro, Cecilia De la Parra, Farhad Merchant, Florent de Dinechin, John L. Gustafson, Martin Langhammer, Rainer Leupers, Sangeeth Nambiar

Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020

Efficient FeFET Crossbar Accelerator for Binary Neural Networks.

Taha Soliman, Ricardo Olivo, Tobias Kirchner, Cecilia De la Parra, Maximilian Lederer, Thomas Kämpfe, Andre Guntoro, Norbert Wehn

Proceedings of the 31st IEEE International Conference on Application-specific Systems, 2020