23 citations · 34 across the 11 of their papers we have counts for
17 papers
DNA Pattern Matching Acceleration with Analog Resistive CAM
Jinane Bazzi, Jana Sweidan, Mohammed E. Fouda +2
DNA pattern matching is essential for many widely used bioinformatics applications. Disease diagnosis is one of these applications, since analyzing changes in DNA sequences can inc…
BackLink: Supervised Local Training with Backward Links
Wenzhe Guo, Mohammed E Fouda, Ahmed M. Eltawil +1
Empowered by the backpropagation (BP) algorithm, deep neural networks have dominated the race in solving various cognitive tasks. The restricted training pattern in the standard BP…
In-memory Associative Processors: Tutorial, Potential, and Challenges
Mohammed E. Fouda, Hasan Erdem Yantir, Ahmed M. Eltawil +1
In-memory computing is an emerging computing paradigm that overcomes the limitations of exiting Von-Neumann computing architectures such as the memory-wall bottleneck. In such para…
Efficient Analog CAM Design
Jinane Bazzi, Jana Sweidan, Mohammed E. Fouda +2
Content Addressable Memories (CAMs) are considered a key-enabler for in-memory computing (IMC). IMC shows order of magnitude improvement in energy efficiency and throughput compare…
In-memory Multi-valued Associative Processor
Mira Hout, Mohammed E. Fouda, Rouwaida Kanj +1
In-memory associative processor architectures are offered as a great candidate to overcome memory-wall bottleneck and to enable vector/parallel arithmetic operations. In this paper…
Resistive Neural Hardware Accelerators
Kamilya Smagulova, Mohammed E. Fouda, Fadi Kurdahi +2
Deep Neural Networks (DNNs), as a subset of Machine Learning (ML) techniques, entail that real-world data can be learned and that decisions can be made in real-time. However, their…